Beginner-friendly collection of Python notebooks for various use cases of machine learning, deep learning, and analytics. For each notebook there is a separate tutorial on the relataly.com blog.

Collection of Notebooks for Natural Language Processing with PyTorch

The complete code and notebooks used for the ACM Recommender Systems Challenge 2019

TensorFlow and Deep Learning Tutorials

Curated implementation notebooks and scripts of deep learning based natural language processing tasks and challenges in TensorFlow.

Jupyter notebooks containing explanation of Machine Learning Algorithms

Notebooks containing examples for different DNN components

TensorFlow implementations of several deep learning models (e.g. variational autoencoder, RNN, ...)

These are the notebook assignments from the deeplearning.ai Tensorflow course on coursera.

Contains different course tutorials and jupyter notebook file for applying different Deep Learning models in different NLP tasks such as text classification, summarization, translation, etc.

Deep Learning Projects using Convolutional, Recurrent, and Generative Adversarial Neural Networks.

Deep Learning Python Notebooks

Notebooks prepared while reading the Deep Learning book

Some DNN model optimization experiments and notebooks

this is the 3 project of the deep learning nanodegree program of udacity

A series of notebooks to familiarize with some important data processing and analysis pipelines based on PyTorch

Deep Learning Machine Learning Templates

Implementation notebooks and scripts of Artistic CNN Models and Generative Models like GANs, VAEs, GMMs, Boltzmann Machine etc. in TensorFlow, and Python. This repo aims to understand and make amazing things out of Neural Network layers.

An Ipython notebook, shows how I solved Tap30 Competition problem by kaggle using Recurrent neural networks.

In this notebook, I implemented a recurrent neural network (Long short-term memory) using PyTorch that performs sentiment analysis.