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

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

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

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

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

Some DNN model optimization experiments and notebooks

Notebooks prepared while reading the Deep Learning book

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

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.

ESESA Notebooks - Primer Trimestre

This repository contains programming assignments for the Deep Learning Specialization by deeplearning.AI. It includes Jupyter Notebooks for exercises in neural networks, hyperparameter tuning, convolutional networks, and sequence models.