BangML Meetup 1: The Path to Becoming an Machine Learning Expert
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This document provides guidance on becoming an ML expert, including: - Taking Andrew Ng's popular ML course on Coursera to get started - Studying mathematics like linear algebra, probability, and statistics - Exploring other online courses and resources on ML from Stanford, edX, and Udacity - Checking GitHub repositories for example codes, tutorials, books, and interesting ML projects - Considering libraries like TensorFlow, scikit-learn, and others for building ML systems
BangML Meetup 1: The Path to Becoming an Machine Learning Expert
- 1. The Path to becoming an ML Expert @dhilipsiva
- 2. Tech Lead, Full-Stack & DevOps - @Appknox I code for Web, Mobile, Embedded & IoT. Open- Source Fanatic. Big Data & Machine Learning Enthusiast. Dad. Atheist So primarily a Developer + little bit of this & that Jack of all trades & Master of none http://dhilipsiva.com dhilipsiva@gmail.com
- 3. I have no idea what I am talking about
- 4. Math - A lot of it Linear Algebra Probability Statistics Also checkout Quora: How do I learn mathematics for machine learning Probabilistic Programming and Bayesian Methods for Hackers
- 5. Andrew Ng's ML Course Andrer Ng is a Computer Scientist His Course on ML is the goto course for Getting Started Formerly a Professor at Stanford University Chief Scientist at Baidu Research Co-Founder of Coursera
- 6. Other Courses Cousera: Machine Learning (Andrew Ng) Stanford: Open Class Room (Andrew Ng) edX: Machine Learning for Data Science and Analytics Udacity: Intro to Machine Learning
- 7. GH Resources Non-Overwhelming Machine Learning Machine Learning for Software Engineers Dive into Machine Learning Machine Learning & Deep Learning Tutorials TensorFlow Book Building Machine Learning Systems with Python Tutorial on scikit-learn and IPython for ML Basic Machine Learning and Deep Learning
- 8. Books with Example Codes on GH Python Machine Learning - Code Machine Learning for Hackers - Code Introduction to Machine Learning with Python - Code Machine Learning in Action - Code
- 10. Libraries worth checking out TensorFlow SciKit Learn Prediction.io Numenta SwiftAI GoLearn AeroSolve pylearn2
- 12. Interesting Code Sample rushter/MLAlgorithms ujjwalkarn/Machine-Learning-Tutorials xviniette/FlappyLearning rasbt/pattern_classi cation ujjwalkarn/DataSciencePython gunthercox/ChatterBot soulmachine/machine-learning-cheat-sheet kootenpv/whereami Newmu/Theano-Tutorials
- 13. Thanks! https://github.com/dhilipsiva/talks Copyright © 2016 dhilipsiva This copy is released under the MIT License Source Code SlideShare Link Questions http://dhilipsiva.com