Top 10 IPython Notebook Tutorials for Data Science and Machine Learning

@machinelearnbot

This is a great project undertaken by Jordi Warmenhoven to implement the concepts from the book An Introduction to Statistical Learning with Applications in R by James, Witten, Hastie, Tibshirani (2013) in Python (the book has practical exercises in R, as you may have guessed). The book is freely available in as a PDF, which makes this repo even more attractive to those looking to learn.


Top 10 IPython Notebook Tutorials for Data Science and Machine Learning

#artificialintelligence

This post is made up of a collection of 10 Github repositories consisting in part, or in whole, of IPython (Jupyter) Notebooks, focused on transferring data science and machine learning concepts. This warmup notebook is from postdoctoral researcher Randal Olson, who uses the common Python ecosystem data analysis/machine learning/data science stack to work with the Iris dataset. Aaron Masino has shared a series of very detailed, very technical machine learning IPython Notebook learning resources. From UC Boulder's Research Computing group, this older collection of notebooks (it's from way back in Fall 2013) covers a wide range of material, with an apparent focus on Linux command line-powered data management.


Top 10 IPython Notebook Tutorials for Data Science and Machine Learning

#artificialintelligence

This is a great project undertaken by Jordi Warmenhoven to implement the concepts from the book An Introduction to Statistical Learning with Applications in R by James, Witten, Hastie, Tibshirani (2013) in Python (the book has practical exercises in R, as you may have guessed). The book is freely available in as a PDF, which makes this repo even more attractive to those looking to learn.


Getting started with Python Machine Learning

#artificialintelligence

Everyone and their mother are learning about machine learning models, classification, neural networks, and Andrew Ng. However, there are wrappers that ease the pain and make working with Theano simple, such as Keras, Blocks and Lasagne. Keras is a fantastic library that provides a high-level API for neural networks and is capable of running on top of either Theano or TensorFlow. Another popular deep learning framework is Torch, which is written in Lua.


Getting started with Python Machine Learning

#artificialintelligence

Machine learning is eating the world right now. Everyone and their mother are learning about machine learning models, classification, neural networks, and Andrew Ng. You've decided you want to be a part of it, but where to start? In this article we'll cover some important characteristics of Python and why it's great for machine learning. We'll also cover some of the most important libraries it has for ML, and if it piques your interest, some places where you can learn more.