MachineLearningTutorials

My Jupyter notebooks from various tutorials in ML

The goal of this repository is to step through tutorials online (1) to learn from them and (2) to repackage them as iPython notebooks (written with Jupyter) so that they are easier to consume and modify.

With that said, most of these tutorials are the result of my curation of other works. I will cite as much as possible but it is safe to assume most of the tutorials come from somewhere else. If you feel I have not properly cited your work, please let me know and I will be happy to update the repo.

A big shout out to the folks at machinelearningmastery.com for providing many of these examples and blogs to help folks get hands on! I really recommend the Keras tutorials as they are a great way to review ML concepts, expand them, and apply them to a great framework. Here's a link: http://machinelearningmastery.com

Here's what you can find in this repo:

• A quick intro to Tensorflow
• Keras introduction
• CNN in Keras

Some subjects I would like to touch on:

• GPU coding and/or Cuda
• Reinforcement learning
• RNNs & LSTM
• Time Series Prediction
• Sequence Classification
• Big Data infrastructure (Hadoop, Spark, cloud ML products, etc.)
• Zeppelin

Future links for tutorials:

• Naive Bayes
• LSTM RNN
• Time-series
• Model Evaluation
• DL & AWS
• Tuning w/ Grid Search
• Ensembling