Deep Learning Playbook

A collection of jupyter notebooks based on my current learning on machine learning and deep learning.

Most of the examples are based on books and other online tutorials.

The notebooks are organized based on frameworks and subject areas:

Keras

• Simple MLP

• Binary classification with MLP

• Multiclass classification with MLP

• Regression with MLP(In Progress)

• Evaluating MLP with scikit-learn

Tensorflow

• Tensorflow Intro

• Simple Tensorflow operations from "Tensorflow For Beginners"

• Simple Logistic Regression from "Tensorflow For Beginners"

Computer Vision

• Computer Vision tutorial

• Scaling image pixel data tutorial

• Evaluate Pixel scaling

• Using built-in image functions in Keras

• Using ImageDataGenerator in Keras intro

• Building ResNet50 in Keras

• A multi-outputs example in Keras

• CNN with Fashion-MNIST dataset in Keras

• CNN with CIFAR-10 dataset in Keras

NLP (Natural Language Processing)

• Simple example of developing Word2Vec embedding using gensim

• Loading GloVe embedding with gensim

• Visualizing Word2Vec embedding

• Simple example of developing embedding using Embedding layer in Keras

• Example of loading GloVe embedding using Embedding layer in Keras

• Example of Debiasing word embeddings

• Example of word vector operations

• Document classification using CNN + Embedding

• Document classification using Multiple CNN + Embedding

• Character-level neural language model generator

• Character-level neural language model

• Word-level neural language model

• Simple neural machine translation NMT example