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MLAI

Getting Started

  1. Install Docker
  2. Install Tensorflow

 

Learn More

 

Intro to Machine Learning

What is Machine Learning? 11min. Played at 1st meeting

Introduction to Machine Learning by Paul Vincent: 1.5hrs

DeepLearning.TV

MOOC

Udacity ML Nano Degree ~ 420 hours

Udacity - Intro to Machine Learning (part of the nano degree): 10 weeks: 6 hrs/wk

Udacity - Deep Learning 12 weeks: 6 hrs/wk

Coursera Andrew NG ML: 11 weeks: ? hrs/wk

Coursera - University of Toronto: Neural Networks for Machine Learning 16 weeks: ? hrs/wk

Machine Learning: Carnegie Mellon - Tom Mitchell and Maria-Florina Balcan: 26 Lectures

EdX - Apache Spark : 3 courses: 10 weeks: 5-10 hrs/wk

EdX - CalTech: Learning from Data(Introductory Machine Learning)

Stanford Machine Learning

Visualizations

Decision Tree Visualization

Neural Network Playground

7 Steps to Mastering Machine Learning with Python

10 Algorithms Machine Learning Engineers Need to Know

EmoVu - emotion recognition

How to score 0.8134 in Titanic Kaggle Challenge

Computerphile - YouTube channel with high level explanations of various subjects in computer science including machine learning

Links from H2O Dallas

H2O came to the Dallas/Plano area for an open tour conference on October 26. Here's the links for the slides and presentations:

 

Podcasts

This Week in Machine Learning & AI

Talking Machines

Interview with Jerry Kaplan - What we need to know about AI

Data Science

Open Source Data Science Masters

https://webdocs.cs.ualberta.ca/~sutton/book/the-book.html

 

Examples

Kaggle

Kaggle was founded as a platform for predictive modeling and analytics competitions on which companies and researchers post their data and statisticians and data miners from all over the world compete to produce the best models. This crowdsourcing approach relies on the fact that there are countless strategies that can be applied to any predictive modeling task and it is impossible to know at the outset which technique or analyst will be most effective.

 

OpenAI Gym

OpenAI Gym is a toolkit for developing and comparing reinforcement learning (RL) algorithms. It consists of a growing suite of environments (from simulated robots to Atari games), and a site for comparing and reproducing results.

 

MLIntroSpark

 MLIntroSpark is the Github Repository containing the code used in the demo on 09/30/2016. The code is commented. Contact Victor Kwak for more info.