Stars
Code and data associated with the book "Statistics for Data Scientists: 50 Essential Concepts"
A collection of inspiring lists, manuals, cheatsheets, blogs, hacks, one-liners, cli/web tools and more.
Roadmap to becoming a data engineer in 2021
🧑🏫 60+ Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), ga…
Leveraging BERT and c-TF-IDF to create easily interpretable topics.
🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
Google Research
A unified framework for machine learning with time series
A game theoretic approach to explain the output of any machine learning model.
Kedro is a toolbox for production-ready data science. It uses software engineering best practices to help you create data engineering and data science pipelines that are reproducible, maintainable,…
Fit interpretable models. Explain blackbox machine learning.
The easiest way to serve AI apps and models - Build reliable Inference APIs, LLM apps, Multi-model chains, RAG service, and much more!
**Unofficial / Community** Kafka Connect MongoDB Sink Connector -> integrated 2019 into the official MongoDB Kafka Connector here: https://www.mongodb.com/kafka-connector
Python Machine Learning Algorithms
Streamlit — A faster way to build and share data apps.
Scrapinghub Learning Center. Report issues in Jira: Report issues in Jira: https://scrapinghub.atlassian.net/projects/WEB
Methods with examples for Feature Selection during Pre-processing in Machine Learning.
Learning to create Machine Learning Algorithms
Simple web app example serving a PyTorch model using streamlit and FastAPI
Sesión de Intepretabilidad de Modelos de Machine Learning con Python para la PyConES2020
Unfolding the Box Model — interactive slides exploring CSS 3D Transforms
This is just a basic algorithms visualizer consisting of 6 sorting algorithms and 4 graph algorithms. Other than HTML, CSS and JS, Jquery and Bootstrap are used in this project.
Self-contained examples of Apache Spark streaming integrated with Apache Kafka.
Awesome Artificial Intelligence, Machine Learning and Deep Learning as we learn it. Study notes and a curated list of awesome resources of such topics.
Anomaly detection related books, papers, videos, and toolboxes