Machine Learning Toolkit

Here is a list of notebooks written in Google Colab of Machine Learning models using toy examples.

Main libraries used: Tensorflow, Keras, CatBoost,

Each notebooks:

• has brief description of the model and implementation.

• can be run in Google Colab.

• is using toy data for educational purposes

Notebook:

• Cat Boost implementation.

• Check GPU in Tensorflow.

• Cuda Setup guide.

• Data Label Encoding for categorical data.

• Keras Checkpoints to do callbacks when training large Deep Learning models.

• Keras embedding layer How it works and how to add it to your Deep Learning Model.

• Keras Generator use when dealing with Big Data. How to plug it to a Deep Learning model.

• Keras Time Distribution Explanation oh how it works and when to use it.

• Keras Tokenizer Example of how to use it and fix the bug.

• Keras Multi GPU Example of how to use GPUs to train your modle in keras.

• Sequesnce To Sequence model. Implementation for translation.

• Text Summarization Prototype using Sequence To Sequence architecture with actual data.

• Neural Network Keras vanila implementation. Toy example with actual data.

• T-pot. - Auto Machine Learning libary.

• Word Embedding* How to load and plot using PCA.