https://github.com/explosion/spaCy
Industrial-strength Natural Language Processing (NLP) with Python and Cython
Python
https://github.com/facebookresearch/fastText
Library for fast text representation and classification.
C++
https://github.com/Smerity/keras_snli
Simple Keras model that tackles the Stanford Natural Language Inference (SNLI) corpus using summation and/or recurrent neural networks
Python
https://github.com/stanfordnlp/spinn
SPINN (Stack-augmented Parser-Interpreter Neural Network): fast, batchable, context-aware TreeRNNs
Python
https://github.com/stanfordnlp/stanza
Stanford NLP group's shared Python tools.
Python
https://github.com/Russell91/nlpcaffe
natural language processing with Caffe
C++
https://github.com/gunthercox/ChatterBot
ChatterBot is a machine learning, conversational dialog engine.
Python
https://github.com/nlp-compromise/nlp_compromise
a cool way to use natural language in javascript
JavaScript
https://github.com/HazyResearch/deepdive
DeepDive
Shell
https://github.com/HazyResearch/mindbender
Tools for iterative knowledge base development with DeepDive
CoffeeScript
https://github.com/vinhkhuc/MemN2N-babi-python
End-To-End Memory Networks for bAbI question-answering tasks
Python
https://github.com/ayoungprogrammer/readAI
A simple AI capable of basic reading comprehension
Python
https://github.com/ayoungprogrammer/nlquery
Natural Language Engine on WikiData
Python
https://github.com/ayoungprogrammer/Lango
Language Lego
Python
https://github.com/bear/parsedatetime
Parse human-readable date/time strings
Python
https://github.com/salestock/fastText.py
A Python interface for Facebook fastText
C++
https://github.com/mikelynn2/sentimentAPI
A fast python scikit-learn text sentiment API server.
Python
https://github.com/dselivanov/text2vec
Fast vectorization, topic modeling, distances and GloVe word embeddings in R.
R
https://github.com/crm416/semantic
A Python library for extracting semantic information from text, such as dates and numbers.
Python
https://github.com/shivam5992/textstat
calculate statistics of text
Python
https://github.com/orenmel/context2vec
context2vec: Learning Generic Context Embedding with Bidirectional LSTM
Python
https://github.com/intel-analytics/TopicModeling
Topic Modeling on Apache Spark
Scala
https://github.com/intel-analytics/InformationExtraction
Information extraction
Java
https://github.com/tudarmstadt-lt/sensegram
Making sense embedding out of word embeddings
Jupyter Notebook
https://github.com/dkpro/dkpro-core-examples
Ready-to-use examples of dkpro-core components and pipelines.
Java
https://github.com/tudarmstadt-lt/JoSimText
A system for word sense induction and disambiguation based on JoBimText approach
Scala
https://github.com/tudarmstadt-lt/lefex
Feature extraction for the JoSimText project: https://github.com/tudarmstadt-lt/JoSimText
Java
https://github.com/policecar/deepDB
Neural tensor network for KB completion ( https://papers.nips.cc/paper/by-source-2013-504 )
Matlab
https://github.com/bigartm/bigartm
Fast topic modeling platform
C++
https://github.com/ziyan/spider
Web Content Extraction Through Machine Learning
TeX
https://github.com/mit-nlp/MITIE
MITIE: library and tools for information extraction
C++
https://github.com/machinalis/quepy
A python framework to transform natural language questions to queries in a database query language.
Python
https://github.com/ceteri/pytextrank
A pure Python impl of TextRank for document summarization
Python
https://github.com/sloria/TextBlob
Simple, Pythonic, text processing--Sentiment analysis, part-of-speech tagging, noun phrase extraction, translation, and more.
Python
https://github.com/Kyubyong/neural_tokenizer
Tokenize English sentences using neural networks.
Python
https://github.com/jaredks/tweetokenize
Tokenization and pre-processing for Twitter data used to train classifiers.
Python
https://github.com/jgc128/DefVectors
A tool for semantic relation extraction. The program finds pairs of semantically related words based on the text definitions coming from the Wikipedia articles (other texts may be also used). The extraction method implemented in this system is based on three similarity measures (cosine, gloss overlap, and Karaulov's measure) between texts and tw…
Python
https://github.com/commonsense/conceptnet5
Code for building ConceptNet from raw data.
Python
https://github.com/mortehu/text-classifier
Creates models to classify documents into categories
Shell
https://github.com/brmson/yodaqa
A Question Answering system built on top of the Apache UIMA framework.
Java
https://github.com/bdhingra/tweet2vec
Twitter hashtag prediction
Python
https://github.com/rlebret/hpca
C++ implementation of the Hellinger PCA for computing word embeddings.
C
https://github.com/aboSamoor/polyglot
Multilingual text (NLP) processing toolkit
Python
https://github.com/dbpedia/fact-extractor
Fact Extraction from Wikipedia Text
Python
https://github.com/anttttti/Wordbatch
Parallel text feature extraction for machine learning
Python
https://github.com/nliu86/word2vec-doc2vec
An extension of word2vec to efficiently represent new text as vectors. New text can be query, sentence and paragraph.
C
https://github.com/arongdari/python-topic-model
Implementation of various topic models
Jupyter Notebook
https://github.com/cjf00000/ScaCTM
Scalable inference for Correlated Topic Models
C++
https://github.com/JonathanRaiman/rsm
Topic analysis using RSM or PVDM.
Python
https://github.com/Conchylicultor/DeepQA
My tensorflow implementation of "A neural conversational model", a Deep learning based chatbot
Python
https://github.com/kootenpv/TwitterQA
My tensorflow implementation of "A neural conversational model", a Deep learning based chatbot
Python
https://github.com/LucasEstevam/CNNSummarizer
Extractive Multi-Document Summarization using Convolutional Neural Networks
Python
https://github.com/smilli/py-corenlp
Python wrapper for Stanford CoreNLP
Python
https://github.com/derekgreene/topic-stability
Stability analysis for topic models
Python
https://github.com/yandex/faster-rnnlm
Faster Recurrent Neural Network Language Modeling Toolkit with Noise Contrastive Estimation and Hierarchical Softmax
C++
https://github.com/commonsense/conceptnet-numberbatch
This is the data from an ensemble that combines ConceptNet, word2vec, and GloVe using a variation on retrofitting.
Python
https://github.com/ianozsvald/learning_text_transformer
Search 'from' and 'to' strings to learn a text cleaning mapping
Python
https://github.com/machinalis/iepy
Information Extraction in Python
Python
https://github.com/seatgeek/fuzzywuzzy
Fuzzy String Matching in Python
Python
https://github.com/bdhingra/ga-reader
Gated Attention Reader for Text Comprehension
Python
https://github.com/joke2k/faker
Faker is a Python package that generates fake data for you.
Python
https://github.com/zygmuntz/phraug2
A new version of phraug, which is a set of simple Python scripts for pre-processing large files
Python
https://github.com/zygmuntz/adversarial-validation
Creating a better validation set when test examples differ from training examples
Python
https://github.com/facebook/bAbI-tasks
Task generation for testing text understanding and reasoning
Lua
https://github.com/spotify/luigi
Luigi is a Python module that helps you build complex pipelines of batch jobs. It handles dependency resolution, workflow management, visualization etc. It also comes with Hadoop support built in.
Python
https://github.com/drivendata/cookiecutter-data-science
A logical, reasonably standardized, but flexible project structure for doing and sharing data science work.
Makefile
https://github.com/iamaziz/PyDataset
Instant access to many datasets.
Python
https://github.com/GoogleCloudPlatform/google-cloud-python
Google Cloud Client Library for Python
Python
https://github.com/ResidentMario/missingno
Missing data visualization module for Python.
Python
https://github.com/HazyResearch/snorkel
A lightweight platform for developing information extraction systems using data programming
Python
https://github.com/stxxl/stxxl
STXXL: Standard Template Library for Extra Large Data Sets
C++
https://github.com/blaze/blaze
NumPy and Pandas interface to Big Data
Python
https://github.com/Parsely/probably
Probabilistic Data Structures in Python (originally presented at PyData 2013)
Python
https://github.com/marcotcr/lime
Lime: Explaining the predictions of any machine learning classifier
JavaScript
https://github.com/tudarmstadt-lt/context-eval
Tools for Evaluation of Unsupervised Word Sense Disambiguation Systems
Jupyter Notebook
https://github.com/cgevans/scikits-bootstrap
Bootstrap Scikit for bootstrap confidence interval estimation.
Python
https://github.com/beamandrew/medical-data
Medical Data for Machine Learning
https://github.com/PyTables/PyTables
A Python package to manage extremely large amounts of data
Python
https://github.com/nok/sklearn-porter
Transpile trained scikit-learn models to C, Java, JavaScript and others.
Python
https://github.com/airbnb/knowledge-repo
A next-generation curated knowledge sharing platform for data scientists and other technical professions.
Python
https://github.com/benhamner/Metrics
Machine learning evaluation metrics, implemented in Python, R, Haskell, and MATLAB / Octave
Python
https://github.com/trevorstephens/gplearn
Genetic Programming in Python, with a scikit-learn inspired API
Python
https://github.com/kaneplusplus/bigmemory
Create, store, access, and manipulate massive matrices. R package.
C++
https://github.com/travisbrady/py-soft-impute
Python implementation of softImpute
Python
https://github.com/wireservice/proof
A Python library for creating fast, repeatable and self-documenting data analysis pipelines.
Python
https://github.com/DEAP/deap
Distributed Evolutionary Algorithms in Python
Python
https://github.com/yandex/ClickHouse
ClickHouse is a free analytic DBMS for big data.
C++
https://github.com/automl/auto-sklearn
automl / auto-sklearn
Python
https://github.com/automl/SMAC3
Sequential Model-based Algorithm Configuration
Python
https://github.com/hyperopt/hyperopt
Distributed Asynchronous Hyperparameter Optimization in Python
Python
https://github.com/erlendd/optomatic
Efficient distributed hyperparameter search library written in Python.
Python
https://github.com/scikit-optimize/scikit-optimize
Sequential model-based optimization with a scipy.optimize interface
Python
https://github.com/sigopt/sigopt_sklearn
SigOpt wrappers for scikit-learn methods
Python
https://github.com/HIPS/Spearmint
Spearmint Bayesian optimization codebase
Python
https://github.com/edublancas/sklearn-evaluation
scikit-learn model evaluation made easy: plots, tables and markdown reports.
Python
https://github.com/amueller/word_cloud
A little word cloud generator in Python
Python
https://github.com/craffel/simple_spearmint
Spearmint, without the gum
Python
https://github.com/HDI-Project/DeepMining
Auto-tuning Data Science Pipelines
HTML
https://github.com/rsteca/sklearn-deap
Use evolutionary algorithms instead of gridsearch in scikit-learn
Python
https://github.com/rhiever/tpot
A Python tool that automatically creates and optimizes machine learning pipelines using genetic programming.
Python
https://github.com/mpearmain/BayesBoost
Bayesian Optimization using xgboost and sklearn API
https://github.com/claesenm/optunity
optimization routines for hyperparameter tuning
Jupyter Notebook
https://github.com/msmbuilder/osprey
Hyperparameter optimization for machine learning pipelines
Python
https://github.com/hyperopt/hyperopt-sklearn
Hyper-parameter optimization for sklearn
Python
https://github.com/fmfn/BayesianOptimization
A Python implementation of global optimization with gaussian processes.
Python
https://github.com/automl/HPOlib
HPOlib is a hyperparameter optimization library. It provides a common interface to three state of the art hyperparameter optimization packages: SMAC, spearmint and hyperopt
Python
https://github.com/rushter/MLAlgorithms
Minimal and clean examples of machine learning algorithms
Python
https://github.com/automl/RoBO
RoBO: a Robust Bayesian Optimization framework
Python
https://github.com/JohnLangford/vowpal_wabbit
Vowpal Wabbit is a machine learning system which pushes the frontier of machine learning with techniques such as online, hashing, allreduce, reductions, learning2search, active, and interactive learning.
C++
https://github.com/spotify/annoy
Approximate Nearest Neighbors in C++/Python optimized for memory usage and loading/saving to disk
C++
https://github.com/google/sensei
Logistic regression engine for medium-sized data
C++
https://github.com/rushter/heamy
A set of useful tools for competitive data science.
Python
https://github.com/tmadl/sklearn-expertsys
Highly interpretable classifiers for scikit learn, producing easily understood decision rules instead of black box models
Python
https://github.com/tmadl/semisup-learn
Semi-supervised learning frameworks for python, which allow fitting scikit-learn classifiers to partially labeled data
Python
https://github.com/TeamHG-Memex/eli5
A library for debugging machine learning classifiers and explaining their predictions
Jupyter Notebook
https://github.com/TeamHG-Memex/sklearn-crfsuite
scikit-learn inspired API for CRFsuite
Python
https://github.com/laurencium/Causalinference
Causal Inference in Python
Python
https://github.com/scikit-learn-contrib/categorical-encoding
A library of sklearn compatible categorical variable encoders
Python
https://github.com/scikit-learn-contrib/hdbscan
A high performance implementation of HDBSCAN clustering.
Jupyter Notebook
https://github.com/scikit-learn-contrib/scikit-learn-contrib
scikit-learn compatible projects
https://github.com/scikit-learn-contrib/imbalanced-learn
Python module to perform under sampling and over sampling with various techniques.
Python
https://github.com/scikit-learn-contrib/lightning
Large-scale linear classification, regression and ranking in Python
Python
https://github.com/scikit-learn-contrib/py-earth
A Python implementation of Jerome Friedman's Multivariate Adaptive Regression Splines
Python
https://github.com/ResidentMario/python-missing-data
NOW A BLOG POST: https://www.residentmar.io/2016/06/12/null-and-missing-data-python.html
Jupyter Notebook
https://github.com/statsmodels/statsmodels
Statsmodels: statistical modeling and econometrics in Python
Python
https://github.com/rasbt/mlxtend
A library of extension and helper modules for Python's data analysis and machine learning libraries.
Python
https://github.com/pystruct/pystruct
Simple structured learning framework for python
Python
https://github.com/numenta/NAB
The Numenta Anomaly Benchmark
Python
https://github.com/numenta/nupic
Numenta Platform for Intelligent Computing: a brain-inspired machine intelligence platform, and biologically accurate neural network based on cortical learning algorithms.
Python
https://github.com/fukatani/stacked_generalization
Library for machine learning stacking generalization.
Python
https://github.com/albahnsen/CostSensitiveClassification
CostSensitiveClassification Library in Python
Python
https://github.com/christophM/rulefit
Python implementation of the rulefit algorithm
Python
https://github.com/NARKOZ/hacker-scripts
Hacker Scripts
JavaScript
https://github.com/mlpack/mlpack
mlpack: a scalable C++ machine learning library
C++
https://github.com/machinalis/featureforge
A set of tools for creating and testing machine learning features, with a scikit-learn compatible API
Python
https://github.com/Sotera/correlation-approximation
Spark implementation of the Google Correlate algorithm to quickly find highly correlated vectors in huge datasets
Scala
https://github.com/larsmans/seqlearn
Sequence learning toolkit for Python
Python
https://github.com/MLWave/Online-Random-Bit-Regression-FTRL
Online Random Bit Regression with FTRL-Proximal in Python
Python
https://github.com/btracey/stackmc
Repository for doing Stacked Monte Carlo on datasets
Go
https://github.com/vecxoz/vecstack
Python package for stacking (machine learning technique)
Python
https://github.com/gatapia/py_ml_utils
Some small utility modules to help with pandas, numpy and sklearn usage in other projects
Python
https://github.com/bingzhengwei/ftrl_proximal_lr
Multithreaded Asynchronous FTRL Proximal Implementation
C++
https://github.com/rhiever/active-categorical-classifier
A tool that evolves small brains capable of scanning and classifying an image.
Jupyter Notebook
https://github.com/airbnb/aerosolve
A machine learning package built for humans.
Java
https://github.com/jundongl/scikit-feature
oepn-source feature selection repository in python (DMML Lab@ASU)
Python
https://github.com/JamesRitchie/scikit-rvm
Relevance Vector Machine implementation using the scikit-learn API.
Python
https://github.com/dclambert/pyensemble
An implementation of Caruana et al's Ensemble Selection algorithm in Python, based on scikit-learn
Python
https://github.com/danielhomola/boruta_py
Python implementations of the Boruta all-relevant feature selection method.
Python
https://github.com/twitter/AnomalyDetection
Anomaly Detection with R
R
https://github.com/all-umass/metric-learn
Metric learning algorithms in Python
Python
https://github.com/jmschrei/pomegranate
Fast, flexible and easy to use probabilistic modelling in Python.
Jupyter Notebook
https://github.com/rth/pysofia
bindings for the sofia-ml machine learning library
C++
https://github.com/johnmyleswhite/BanditsBook
Code for my book on Multi-Armed Bandit Algorithms
R
https://github.com/nicodv/kmodes
Python implementations of the k-modes and k-prototypes clustering algorithms, for clustering categorical data
Python
https://github.com/qminer/qminer
Analytic platform for real-time large-scale streams containing structured and unstructured data.
C++
https://github.com/bashtage/arch
ARCH models in Python
Python
https://github.com/gallantlab/pyrcca
Regularized kernel canonical correlation analysis in Python
Jupyter Notebook
https://github.com/donlnz/nonconformist
Python implementation of the conformal prediction framework.
Python
https://github.com/ajbc/spf
Social Poisson Factorization
C++
https://github.com/davmre/treegp
Gaussian Process Regression for Python/Numpy
Python
https://github.com/alkant/cpm
Convex Polytope Machine
C++
https://github.com/mmoussallam/bird
Pure Python implementation of the BIRD algorithm for (structured)-sparsity based denoising of multichannel array
Python
https://github.com/dmarx/Topological-Anomaly-Detection
Topological Anomaly Detection (TAD) per Gartley and Basener 2009
Python
https://github.com/claesenm/EnsembleSVM
A Library for Ensemble Learning Using Support Vector Machines
C++
https://github.com/keenon/lense
A framework for solving tasks with a real-time human-ML hybrid
Java
https://github.com/hmmlearn/hmmlearn
Hidden Markov Models in Python, with scikit-learn like API
Python
https://github.com/linkedin/FeatureFu
Library and tools for advanced feature engineering
Java
https://github.com/lensacom/sparkit-learn
PySpark + Scikit-learn = Sparkit-learn
Python
https://github.com/yandex/rep
Machine Learning toolbox for Humans
Jupyter Notebook
https://github.com/arogozhnikov/hep_ml
Machine learning algorithms for high energy physics.
Jupyter Notebook
https://github.com/mayou36/raredecay
Machine Learning tools on top of REP
Jupyter Notebook
https://github.com/ibab/python-mle
A Python package for performing Maximum Likelihood Estimates
Python
https://github.com/scikit-learn-contrib/forest-confidence-interval
Confidence intervals for scikit-learn forest algorithms
Python
https://github.com/IBCNServices/GENESIM
An innovative technique that constructs an ensemble of decision trees and converts this ensemble into a single, interpretable decision tree with an enhanced predictive performance
Scilab
https://github.com/baidu/fast_rgf
Multi-core implementation of Regularized Greedy Forest
C++
https://github.com/tmadl/sklearn-random-rotation-ensembles
Scikit-learn compatible implementations of the Random Rotation Ensemble idea of (Blaser & Fryzlewicz, 2016)
Python
https://github.com/tmadl/sklearn-random-bits-forest
Scikit-learn compatible wrapper of the Random Bits Forest program written by (Wang et al., 2016)
Python
https://github.com/fukatani/rgf_python
Python Wrapper of Regularized Greedy Forest.
Python
https://github.com/MLWave/RGF-sklearn
Scikit-learn API toy wrapper for Regularized Greedy Forests
Python
https://github.com/MLWave/extremely-simple-one-shot-learning
Extremely simple one-shot learning in Python
Python
https://github.com/takuti/stream-feature-selection
Implementation of unsupervised feature selection algorithm proposed by [Huang, et al. 2015]
Jupyter Notebook
https://github.com/balajiln/mondrianforest
Code for Mondrian Forests (for classification and regression)
Python
https://github.com/mhahsler/recommenderlab
recommenderlab - Lab for Developing and Testing Recommender Algorithms - R package
R
https://github.com/imbs-hl/ranger
A Fast Implementation of Random Forests
C++
https://github.com/aloysius-lim/bigrf
Random forests for R for large data sets, optimized with parallel tree-growing and disk-based memory
R
https://github.com/ajtulloch/sklearn-compiledtrees
Compiled Decision Trees for scikit-learn
Python
https://github.com/ttomita/RandomerForest
Discriminant Projection Forest results, datasets, etc.
Matlab
https://github.com/andrewclegg/mondrianforest
Code for "Mondrian Forests: Efficient Online Random Forests"
Python
https://github.com/ajverster/RotationForest
An implementation of the Rotation Forest algorithm from Rodriguez et al. 2006
R
https://github.com/Evfro/polara
Recommender system and evaluation framework for top-n recommendations tasks that respects polarity of feedbacks. Fast, flexible and easy to use. Written in python, boosted by scientific python stack.
Python
https://github.com/lyst/lightfm
A Python implementation of LightFM, a hybrid recommendation algorithm.
Python
https://github.com/Mendeley/mrec
A recommender systems development and evaluation package by Mendeley
Python
https://github.com/scikit-learn-contrib/polylearn
A library for factorization machines and polynomial networks for classification and regression in Python.
Python
https://github.com/coreylynch/pyFM
Factorization machines in python
Python
https://github.com/comadan/FM_FTRL
Hashed Factorization Machine with Follow The Regularized Leader for Kaggle Avazu Click-Through Rate Competition
Python
https://github.com/srendle/libfm
Library for factorization machines
C++
https://github.com/arthurmensch/modl
Randomized online matrix factorization
Python
https://github.com/sckangz/recom_mc
this is the code for AAAI 2016 paper: Top-N Recommender System via Matrix Completion
Matlab
https://github.com/cjlin1/libmf
LIBMF is a library for large-scale sparse matrix factorization.
C++
https://github.com/manasRK/word2vec-recommender
Recommendation engine based on contextual word embeddings
Python
https://github.com/recsyschallenge/2016
RecSys Challenge 2016: job recommendations
TeX
https://github.com/mattdennewitz/playlist-to-vec
An artist recommendation engine, from feeding Spotify playlists through word2vec
Python
https://github.com/ibayer/fastFM
fastFM: A Library for Factorization Machines
Python
https://github.com/benfred/implicit
Fast Python Collaborative Filtering for Implicit Datasets
Python
https://github.com/quora/qmf
A fast and scalable C++ library for implicit-feedback matrix factorization models
C++
https://github.com/MrChrisJohnson/implicit-mf
Implicit matrix factorization as outlined in https://yifanhu.net/PUB/cf.pdf.
Python
https://github.com/songgc/TF-recomm
Tensorflow-based Recommendation systems
Python
https://github.com/tobegit3hub/deep_recommend_system
Deep learning recommend system with TensorFlow
Python
https://github.com/turi-code/python-libffm
A Python wrapper for the libffm library.
C++
https://github.com/sanealytics/recommenderlabrats
Some recommendation algorithms and research
R
https://github.com/yixuan/recosystem
Recommender System Using Parallel Matrix Factorization
C++
https://github.com/ocelma/python-recsys
A python library for implementing a recommender system
Python
https://github.com/trungngv/gpfm
Gaussian Process Factorization Machines for Context-aware Recommendations
Matlab
https://github.com/mblondel/spira
Recommender systems in Python
C
https://github.com/kyrre/ctr
collaborative topic regression with social matrix factorization
C++
https://github.com/chyikwei/recommend
recommendation system with python
Python
https://github.com/markusweimer/cofirank
CoFiRank -- Collaborative Filtering for Ranking
C++
https://github.com/Evfro/fifty-shades
Source code to support ACM RecSys'16 paper "Fifty Shades of Ratings: How to Benefit from a Negative Feedback in Top-N Recommendations Tasks"
Jupyter Notebook
https://github.com/yanpanlau/DDPG-Keras-Torcs
Using Keras and Deep Deterministic Policy Gradient to play TORCS
Python
https://github.com/facebook/MemNN
Memory Networks implementations
Lua
https://github.com/jxwufan/AssociativeRetrieval
TensorFlow implementation of Fast Weights
Python
https://github.com/baidu-research/persistent-rnn
Fast Recurrent Networks Library
C++
https://github.com/ferrine/gelato
Bayesian desert for Lasagne
Python
https://github.com/jimfleming/recurrent-entity-networks
An implementation of "Tracking the World State with Recurrent Entity Networks".
Python
https://github.com/jiamings/fast-weights
Implementation of the paper Using Fast Weights to Attend to the Recent Past
Python
https://github.com/iassael/learning-to-communicate
Learning to Communicate with Deep Multi-Agent Reinforcement Learning
Lua
https://github.com/HFTrader/DeepLearningBook
MIT Deep Learning Book in PDF format
https://github.com/CuriousAI/ladder
Ladder network is a deep learning algorithm that combines supervised and unsupervised learning
Python
https://github.com/CuriousAI/tagger
Deep Unsupervised Perceptual Grouping
Jupyter Notebook
https://github.com/emansim/unsupervised-videos
Unsupervised Learning of Video Representations using LSTMs
Cuda
https://github.com/aditya-grover/node2vec
word2vec
Python
https://github.com/thomasmesnard/DeepMind-Teaching-Machines-to-Read-and-Comprehend
Implementation of "Teaching Machines to Read and Comprehend" proposed by Google DeepMind
Python
https://github.com/hidasib/GRU4Rec
GRU4Rec is the cleaned & simplified implementation of the algorithm of the "Session-based Recommendations with Recurrent Neural Networks" paper, published at ICLR 2016. The code is stripped of features that we had found to be unhelpful in increasing accuracy.
Python
https://github.com/seomoz/word2gauss
Gaussian word embeddings
Python
https://github.com/tflearn/tflearn
Deep learning library featuring a higher-level API for TensorFlow.
Python
https://github.com/tiny-dnn/tiny-dnn
header only, dependency-free deep learning framework in C++11
C++
https://github.com/tensorflow/skflow
Simplified interface for TensorFlow (mimicking Scikit Learn) for Deep Learning
Python
https://github.com/Maratyszcza/NNPACK
Acceleration package for neural networks on multi-core CPUs
C
https://github.com/Microsoft/LightGBM
A fast, distributed, high performance gradient boosting (GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks. It is under the umbrella of the DMTK(https://github.com/microsoft/dmtk) project of Microsoft.
C++
https://github.com/ArdalanM/pyLightGBM
Python binding for Microsoft LightGBM
Jupyter Notebook
https://github.com/thomaskeck/FastBDT
Stochastic Gradient Boosted Decision Trees as Standalone, TMVAPlugin and Python-Interface
C++
https://github.com/mirri66/xgbmagic
Pandas dataframe goes in, XGBoost model results come out
Python
https://github.com/dmlc/xgboost
Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Flink and DataFlow
C++
https://github.com/limexp/xgbfir
XGBoost Feature Interactions Reshaped
Python
https://github.com/google/deepboost
Deep Boosting
C++
https://github.com/amirsaffari/online-multiclass-lpboost
Online Multi-Class LPBoost and Gradient Boosting
C++
https://github.com/DmitryUlyanov/Multicore-TSNE
Parallel t-SNE implementation with Python and Torch wrappers.
C++
https://github.com/facebook/fbpca
Fast Randomized PCA/SVD
Python
https://github.com/zygmuntz/dimensionality-reduction-for-sparse-binary-data
convert a lot of zeros and ones to fewer real numbers
Python
https://github.com/lisitsyn/tapkee
A flexible and efficient С++ template library for dimension reduction
C++
https://github.com/esafak/mca
Multiple correspondence analysis
Python
https://github.com/allentran/pca-magic
PCA that iteratively replaces missing data
Python
https://github.com/blue-yonder/tsfresh
Automatic extraction of relevant features from time series:
Python
https://github.com/cesium-ml/cesium
Machine Learning Time-Series Platform
Python
https://github.com/alexminnaar/time-series-classification-and-clustering
Time series classification and clustering code written in Python. Mostly based on the work of Dr. Eamonn Keogh at University of California Riverside
Jupyter Notebook
https://github.com/bytefish/timeseries
Dynamic Time Warping (DTW) in C++
C++
https://github.com/hildensia/bayesian_changepoint_detection
Methods to get the probability of a changepoint in a time series.
Jupyter Notebook
https://github.com/markdregan/K-Nearest-Neighbors-with-Dynamic-Time-Warping
Python implementation of KNN and DTW classification algorithm
Python
https://github.com/Netflix/atlas
In-memory dimensional time series database.
Scala
https://github.com/AmazaspShumik/sklearn-bayes
Python package for Bayesian Machine Learning with scikit-learn API
Jupyter Notebook
https://github.com/DartML/Stein-Variational-Gradient-Descent
code for the paper "Stein Variational Gradient Descent (SVGD): A General Purpose Bayesian Inference Algorithm"
Python
https://github.com/davpinto/regularizedgb
Regularized Gaussian Bayes Classifier (RGB) using the Ledoit-Wolf shrinkage estimator of covariance matrix
R
https://github.com/pymc-devs/pymc3
Probabilistic Programming in Python. Uses Theano as a backend, supports NUTS and ADVI.
Python
https://github.com/dsteinberg/libcluster
An extensible C++ library of Hierarchical Bayesian clustering algorithms, such as Bayesian Gaussian mixture models, variational Dirichlet processes, Gaussian latent Dirichlet allocation and more.
C++
https://github.com/aloctavodia/Doing_bayesian_data_analysis
Python/PyMC3 versions of the programs described in Doing bayesian data analysis by John K. Kruschke
Jupyter Notebook
https://github.com/olgabot/prettyplotlib
Painlessly create beautiful matplotlib plots.
Python
https://github.com/altair-viz/altair
Declarative statistical visualization library for Python
Jupyter Notebook
https://github.com/MLWave/kepler-mapper
KeplerMapper is a Python class for visualization of high-dimensional data and 3-D point cloud data.
Python
https://github.com/airbnb/superset
Superset is a data exploration platform designed to be visual, intuitive, and interactive
Python
https://github.com/lferry007/LargeVis
visualize large-scale and high-dimensional data
C++
https://github.com/glumpy/glumpy
Python+Numpy+OpenGL: fast, scalable and beautiful scientific visualization
Python
https://github.com/cornelltech/snack
Stochastic Neighbor and Crowd Kernel (SNaCK) embeddings: Quick and dirty visualization of large-scale datasets via concept embeddings
C++
https://github.com/vispy/vispy
High-performance interactive 2D/3D data visualization library
Python
https://github.com/Developer-Y/cs-video-courses
List of Computer Science courses with video lectures.
Papers from the computer science community to read and discuss.
https://github.com/papers-we-love/papers-we-love
https://github.com/AI-ON/ai-on.org
AI•ON projects repository and website source.
https://github.com/prakhar1989/awesome-courses
📚 List of awesome university courses for learning Computer Science!
https://github.com/owainlewis/awesome-artificial-intelligence
A curated list of Artificial Intelligence (AI) courses, books, video lectures and papers
https://github.com/rossant/awesome-math
A curated list of awesome mathematics resources
Python
https://github.com/rushter/data-science-blogs
A curated list of data science blogs
Python
https://github.com/josephmisiti/awesome-machine-learning
A curated list of awesome Machine Learning frameworks, libraries and software.
Python
https://github.com/kjw0612/awesome-random-forest
Random Forest - a curated list of resources regarding random forest
https://github.com/jakevdp/PythonDataScienceHandbook
Jupyter Notebooks for the Python Data Science Handbook
Jupyter Notebook
https://github.com/EderSantana/awesomeMLmath
Curated list to learn the math basics for machine learning
https://github.com/ZuzooVn/machine-learning-for-software-engineers
A complete daily plan for studying to become a machine learning engineer.
https://github.com/bulutyazilim/awesome-datascience
📝 An awesome Data Science repository to learn and apply for real world problems.
https://github.com/donnemartin/data-science-ipython-notebooks
Continually updated data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.
Python
https://github.com/Quartz/bad-data-guide
An exhaustive reference to problems seen in real-world data along with suggestions on how to resolve them.
https://github.com/hangtwenty/dive-into-machine-learning
Dive into Machine Learning with Python Jupyter notebook and scikit-learn
https://github.com/jadianes/spark-py-notebooks
Apache Spark & Python (pySpark) tutorials for Big Data Analysis and Machine Learning as IPython / Jupyter notebooks
Jupyter Notebook
https://github.com/ogrisel/parallel_ml_tutorial
Tutorial on scikit-learn and IPython for parallel machine learning
Jupyter Notebook
https://github.com/johnmyleswhite/ML_for_Hackers
Code accompanying the book "Machine Learning for Hackers"
R
https://github.com/johnmyleswhite/MLNotes
Very concise notes on machine learning and statistics.
R
https://github.com/savarin/pyconuk-introtutorial
practical introduction to pandas and scikit-learn via Kaggle problems
Jupyter Notebook
https://github.com/ResidentMario/watsongraph-tutorial
Tutorial materials for the watsongraph library.
Jupyter Notebook
https://github.com/ujjwalkarn/DataSciencePython
common data analysis and machine learning tasks using python
Python
https://github.com/caesar0301/awesome-public-datasets
An awesome list of high-quality open datasets in public domains (on-going).
https://github.com/richarddmorey/ConfidenceIntervalsFallacy
The Fallacy of Placing Confidence in Confidence Intervals
HTML
https://github.com/ujjwalkarn/Machine-Learning-Tutorials
machine learning and deep learning tutorials, articles and other resources
https://github.com/jxieeducation/DIY-Data-Science
Machine Learning Tool Guides and Theory Notes
https://github.com/albahnsen/PracticalMachineLearningClass
Practical Machine Learning
Jupyter Notebook
https://github.com/albahnsen/ML_RiskManagement
Short Course - Applied Machine Learning for Risk Management
Jupyter Notebook
https://github.com/rasbt/pattern_classification
A collection of tutorials and examples for solving and understanding machine learning and pattern classification tasks
Jupyter Notebook
https://github.com/frnsys/ai_notes
machine learning/artificial intelligence notes
Jupyter Notebook
https://github.com/TheGrimmScientist/AgileMachineLearning
The main repo for Hack University's Summer '16 Agile Machine Learning class
Python
https://github.com/open-source-society/data-science
📊 Path to a free self-taught education in Data Science!
https://github.com/gkamradt/Lessons-Learned-Data-Science-Interviews
Lessons learned the hard way through over 30+ data science interviews
https://github.com/grahamjenson/list_of_recommender_systems
A List of Recommender Systems and Resources
https://github.com/jvns/pandas-cookbook
Recipes for using Python's pandas library
https://github.com/diefimov/MTH594_MachineLearning
The materials for the course MTH 594 Advanced data mining: theory and applications (Dmitry Efimov, American University of Sharjah)
Jupyter Notebook
https://github.com/ageron/handson-ml
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in python using Scikit-Learn and TensorFlow.
Jupyter Notebook
https://github.com/rhiever/Data-Analysis-and-Machine-Learning-Projects
Repository of teaching materials, code, and data for my data analysis and machine learning projects.
Jupyter Notebook
https://github.com/amitkaps/hackermath
Introduction to Statistics and Basics of Mathematics for Data Science - The Hacker's Way
Jupyter Notebook
https://github.com/rasbt/python-machine-learning-book
The "Python Machine Learning" book code repository and info resource
Jupyter Notebook
https://github.com/rlabbe/statistical-rethinking
Notebooks containing R code from Richard McElreath's Statistical Rethinking
Jupyter Notebook
https://github.com/fasouto/awesome-dataviz
📈 A curated list of awesome data visualization libraries and resources.
https://github.com/wnzhang/rtb-papers
A collection of research and survey papers of real-time bidding (RTB) based display advertising techniques.
https://github.com/oreillymedia/t-SNE-tutorial
A tutorial on the t-SNE learning algorithm
JavaScript
https://github.com/duvenaud/phd-thesis
Automatic Model Construction with Gaussian Processes
TeX
https://github.com/memo/ai-resources
Selection of resources to learn Artificial Intelligence / Machine Learning / Statistical Inference / Deep Learning / Reinforcement Learning
https://github.com/esokolov/ml-course-hse
Машинное обучение на ФКН ВШЭ
Jupyter Notebook
https://github.com/esokolov/ml-course-msu
Lecture notes and code for Machine Learning practical course on CMC MSU
Jupyter Notebook
https://github.com/vkantor/MIPT_Data_Mining_In_Action_2016
"Data Mining in Action Course", Moscow Institute of Physics and Technologies
Jupyter Notebook
https://github.com/elejke/ML_tasks
Machine Learning IITP RAS course 2015
https://github.com/glouppe/phd-thesis
Repository of the thesis "Understanding Random Forests"
TeX
https://github.com/demidovakatya/vvedenie-mashinnoe-obuchenie
📝 Подборка ресурсов по машинному обучению
https://github.com/Dyakonov/ml_hacks
Приёмы в машинном обучении
Jupyter Notebook
https://github.com/joelgrus/data-science-from-scratch
code for Data Science From Scratch book
Python
https://github.com/yandexdataschool/REP_tutorial
Examples of using yandex/rep framework
Jupyter Notebook
https://github.com/arogozhnikov/cats
Test of algorithms on highly-categorical data
Jupyter Notebook
https://github.com/rougier/numpy-100
100 numpy exercises (100% complete)
Jupyter Notebook
https://github.com/svaksha/pythonidae
Curated decibans of scientific programming resources in Python.
https://github.com/onurakpolat/awesome-bigdata
A curated list of awesome big data frameworks, ressources and other awesomeness.
https://github.com/engineerapart/TheRemoteFreelancer
Listing of community-curated resources to find topical remote freelance & contract work for software developers, web designers, and more!
https://github.com/dennybritz/startupreadings
Reading list for all things startup-related
https://github.com/jessicard/remote-jobs
A list of semi to fully remote-friendly companies in tech
https://github.com/lukasz-madon/awesome-remote-job
A curated list of awesome remote jobs and resources. Inspired by https://github.com/vinta/awesome-python
https://github.com/hugo53/awesome-RemoteWork
Resources for remote workers: approaches, hiring page, remote life and more.
https://github.com/charlesfeng/startup-school-notes
Startup school notes by Charles Feng
https://github.com/songrotek/Deep-Learning-Papers-Reading-Roadmap
Deep Learning papers reading roadmap for anyone who are eager to learn this amazing tech!
Python
https://github.com/jtoy/awesome-tensorflow
TensorFlow - A curated list of dedicated resources https://tensorflow.org
https://github.com/dennybritz/deeplearning-papernotes
Summaries and notes on Deep Learning research papers
https://github.com/kjw0612/awesome-rnn
Recurrent Neural Network - A curated list of resources dedicated to RNN
https://github.com/robertsdionne/neural-network-papers
neural-network-papers
https://github.com/ChristosChristofidis/awesome-deep-learning
A curated list of awesome Deep Learning tutorials, projects and communities.
https://github.com/iassael/learning-to-communicate
Learning to Communicate with Deep Multi-Agent Reinforcement Learning
Lua
https://github.com/karpathy/paper-notes
Random notes on papers, likely a short-term repo.
https://github.com/sbrugman/deep-learning-papers
Papers about deep learning ordered by task, date. Current state-of-the-art papers are labelled.
https://github.com/gokceneraslan/awesome-deepbio
A curated list of awesome deep learning applications in the field of computational biology
https://github.com/arokem/try-tf
Simple code for trying out TensorFlow with simulated datasets
Jupyter Notebook
https://github.com/aymericdamien/TensorFlow-Examples
TensorFlow Tutorial and Examples for beginners
Jupyter Notebook
https://github.com/MaxwellRebo/awesome-2vec
Curated list of 2vec-type embedding models
https://github.com/terryum/awesome-deep-learning-papers
Awesome Deep Learning Papers
https://github.com/joanbruna/stat212b
Topics Course on Deep Learning UC Berkeley
https://github.com/daviddao/awesome-very-deep-learning
A curated list of papers and code about very deep neural networks (especially ResNets and DenseNets) 😎
https://github.com/lisa-lab/DeepLearningTutorials
Deep Learning Tutorial notes and code. See the wiki for more info.
Python
https://github.com/jatinshah/ufldl_tutorial
Stanford Unsupervised Feature Learning and Deep Learning Tutorial
Python
https://github.com/aikorea/awesome-rl
Reinforcement learning resources curated
https://github.com/dennybritz/reinforcement-learning
Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accompany Sutton's Book and David Silver's course.
Jupyter Notebook
https://github.com/carpedm20/deep-rl-tensorflow
TensorFlow implementation of Deep Reinforcement Learning papers
Python
https://github.com/ReactiveCJ/BayesianLearning
Bayesian Machine Learning
https://github.com/CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers
aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)
Jupyter Notebook
https://github.com/keonkim/awesome-nlp
📖 A curated list of resources dedicated to Natural Language Processing (NLP)
https://github.com/anuzzolese/oke-challenge-2016
ESWC-16 Open Knowledge Extraction (OKE) Challenge
https://github.com/anuzzolese/oke-challenge
Guidelines for OKE-challenge@ESWC2015
https://github.com/deepmind/rc-data
Question answering dataset featured in "Teaching Machines to Read and Comprehend
Python
https://github.com/unnati-xyz/intro-to-deep-learning-for-nlp
The repository contains code walkthroughs which introduces Deep Learning in the field of Natural Language Processing.
Jupyter Notebook
https://github.com/totalgood/pycon-2016-nlp-tutorial
PyCon 2016 Tutorial Session -- Making Connections with Natural Language Processing
Jupyter Notebook
https://github.com/totalgood/nlpia
NLP in action
Python
https://github.com/tudarmstadt-lt/courses
Source code of projects related to courses taught by LT
JavaScript
https://github.com/evanmiltenburg/python-for-text-analysis
If you want to use Python for text analysis, this course is for you!
Jupyter Notebook
https://github.com/rouseguy/DeepLearningNLP_Py
Introduction to Deep Learning for Natural Language Processing
Jupyter Notebook
https://github.com/shashankg7/Deep-Learning-for-NLP-Resources
List of resources to get started with Deep Learning for NLP.
https://github.com/linanqiu/word2vec-sentiments
Tutorial for Sentiment Analysis using Doc2Vec in gensim (or "getting 87% accuracy in sentiment analysis in under 100 lines of code")
Jupyter Notebook
https://github.com/bogatyy/cs224d
Code for Stanford CS224D: deep learning for natural language understanding
Python
https://github.com/andrewt3000/DL4NLP
Deep Learning for NLP resources
https://github.com/nyu-dl/NLP_DL_Lecture_Note
Natural Language Understanding with Distributed Representation
TeX
https://github.com/hal3/vwnlp
Solving NLP problems with Vowpal Wabbit: Tutorial and more
Jupyter Notebook
https://github.com/sindresorhus/awesome
😎 Curated list of awesome lists
https://github.com/dennybritz/booknotes
Notes I'm taking when reading books
https://github.com/tiimgreen/github-cheat-sheet
A list of cool features of Git and GitHub.
https://github.com/jwasham/google-interview-university
A complete daily plan for studying to become a Google software engineer.
https://github.com/bayandin/awesome-awesomeness
A curated list of awesome awesomeness
https://github.com/bmtgoncalves/Mining-Georeferenced-Data
A hands on guide on using Python to collect, analyse and mine geo-referenced data from location based services (e.g. Foursquare, Twitter) and the Sharing Economy (Uber, Airbnb etc.).
https://github.com/Kiloreux/awesome-robotics
A list of awesome Robotics resources
https://github.com/ptwobrussell/Mining-the-Social-Web-2nd-Edition
The official online compendium for Mining the Social Web, 2nd Edition (O'Reilly, 2013)
Ruby
https://github.com/matiassingers/awesome-readme
A curated list of awesome READMEs
https://github.com/wilsonfreitas/awesome-quant
A curated list of insanely awesome libraries, packages and resources for Quants (Quantitative Finance)
https://github.com/andreis/interview
Everything you need to kick ass on your coding interview
https://github.com/space10-community/conversational-form
Turning web forms into conversations
HTML
https://github.com/cassidoo/interview
Everything you need to kick butt on your coding interview
https://github.com/MaximAbramchuck/awesome-interview-questions
A curated awesome list of lists of interview questions. Feel free to contribute! 🎓
https://github.com/Smerity/yolo-cpp
YOLO C++: A crash course for those needing to learn street fighting C++
C++
https://github.com/kamyu104/LeetCode
📝 Python / C++ 11 Solutions of All 434 LeetCode Questions
Python
https://github.com/vinta/awesome-python
A curated list of awesome Python frameworks, libraries, software and resources
Python
https://github.com/nryoung/algorithms
An educational library of algorithms in Python
Python
https://github.com/fffaraz/awesome-cpp
A curated list of awesome C/C++ frameworks, libraries, resources, and shiny things. Inspired by awesome-... stuff.
https://github.com/donnemartin/interactive-coding-challenges
Continually updated, interactive, test-driven Python coding interview challenges (algorithms and data structures).
Python
https://github.com/quantifiedcode/python-anti-patterns
An open collection of Python anti-patterns and "worst practices", many of which can be checked automatically on QuantifiedCode
https://github.com/rigtorp/awesome-modern-cpp
A collection of resources on modern C++
HTML
https://github.com/Dyakonov/python_hacks
Различные приёмы при написании python-программ.
Jupyter Notebook
https://github.com/owocki/pytrader
cryptocurrency trading robot
Python
https://github.com/jflesch/paperwork
📎 Using scanners and OCR to grep paper documents the easy way
Python
https://github.com/codelucas/newspaper
News, full-text, and article metadata extraction in Python 3
Python
https://github.com/pybind/pybind11
Seamless operability between C++11 and Python
C++
https://github.com/metachris/pdfx
Extract references (pdf, url, doi, arxiv) and metadata from a PDF; optionally download all referenced PDFs
Python
https://github.com/ResidentMario/watsongraph
Concept discovery and recommendation library built on top of the IBM Watson cognitive API.
Python
https://github.com/p-e-w/maybe
📂 🐇 🎩 See what a program does before deciding whether you really want it to happen.
Python
https://github.com/minimaxir/facebook-page-post-scraper
Data scraper for Facebook Pages, and also code accompanying the blog post How to Scrape Data From Facebook Page Posts for Statistical Analysis
Python
https://github.com/mementum/backtrader
Python Backtesting library for trading strategies
Python
https://github.com/quantopian/zipline
Zipline, a Pythonic Algorithmic Trading Library
Python
https://github.com/deependersingla/deep_trader
This project uses reinforcement learning on stock market and agent tries to learn trading. The goal is to check if the agent can learn to read tape. The project is dedicated to hero in life great Jesse Livermore.
Python
https://github.com/tbenthompson/cppimport
Import C++ files directly from Python!
Python
https://github.com/yahoo/mdbm
MDBM a very fast memory-mapped key/value store.
C++
https://github.com/dennybritz/sentiment-analysis
Japanese Sentiment Analysis
Jupyter Notebook
https://github.com/zygmuntz/numer.ai
Validation and prediction code for numer.ai
Python
https://github.com/jimfleming/numerai
Code from my experiments on Numerai
Jupyter Notebook
https://github.com/awslabs/machine-learning-samples
Sample applications built using Amazon Machine Learning.
Python
https://github.com/ericchiang/churn
Code accompanying blog post
Python
https://github.com/felixlaumon/kaggle-right-whale
2nd place solution to the Kaggle Right Whale challenge
Python
https://github.com/trinker/sentimentr
sentimentr is designed to quickly calculate text polarity sentiment at the sentence level and optionally aggregate by rows or grouping variable(s).
https://github.com/echen/link-prediction
Solution to Facebook's link prediction contest on Kaggle.
Scala
https://github.com/pratik008/HealthCare_Twitter_Analysis
Healthcare Twitter Analysis Initial Files
Python
https://github.com/RaRe-Technologies/movie-plots-by-genre
Movie plots by genre tutorial at PyData Berlin 2016
Jupyter Notebook
https://github.com/gsingers/rtfmbot
Because we're all tired of answering questions when people should clearly RTFM.
Python
https://github.com/ceteri/ChicagoCrime
predictive modeling for crime rates in Chicago wards
R
https://github.com/kaz-Anova/ensemble_amazon
Code to share different ensemble techniques with focus on meta-stacking , using data from Amazon.com - Employee Access Challenge kaggle competition
Python
https://github.com/MLWave/Kaggle-Ensemble-Guide
Code for the Kaggle Ensembling Guide Article on MLWave
Python
https://github.com/diefimov/west_nile_virus_2015
the 2nd place solution for West Nile Virus Prediction challenge on Kaggle
C++
https://github.com/Far0n/kaggletils
kaggletils
Python
https://github.com/entron/entity-embedding-rossmann
This is the code used in the paper "Entity Embeddings of Categorical Variables".
Jupyter Notebook
https://github.com/grfiv/healthcare_twitter_analysis
Healthcare Twitter Analysis
Jupyter Notebook
https://github.com/saffsd/kaggle-stumbleupon2013
Entry to the Kaggle 2013 StumbleUpon competition. Ranked 4th on the final private leaderboard.
Python
https://github.com/KirkHadley/SectorRotation
RF + GBM + ARIMA/NN Hybrid ensemble for predicting 6-month returns for the 9 sector ETFs plus IYZ
Python
https://github.com/harpribot/deep-summarization
Uses Recurrent Neural Network (LSTM/GRU/basic_RNN units) for summarization of amazon reviews
Python
https://github.com/Dyakonov/timeseries
временные ряды
Jupyter Notebook
https://github.com/Dyakonov/case_shmid
анализ кардиограмм
Jupyter Notebook
https://github.com/Dyakonov/case_sdsj
Решение задачи конкурса Сбербанка
Jupyter Notebook
https://github.com/Dyakonov/case_SmartRecruits
Определение эффективности менеджера
Jupyter Notebook
https://github.com/Cardal/Kaggle_AllenAIscience
My solution for the Kaggle "Allen AI science challenge"
Python
https://github.com/Cardal/Kaggle_WestNileVirus
Winning solution for the Kaggle "West Nile Virus" competition (2015)
Python
https://github.com/gdb/kaggle
A collection of Kaggle solutions. Not very polished.
Python
https://github.com/chrischris292/ShowMeTheMoney
A Sentiment Analysis Tool on Financial Data
JavaScript