Machine Learning Guide and Tutorial for Software Engineers
This article was written by Nam Vu on GitHub.
What is it?
This is my multi-month study plan for going from mobile developer (self-taught, no CS degree) to machine learning engineer.My main goal was to find an approach to studying Machine Learning that is mainly hands-on and abstracts most of the Math for the beginner. This approach is unconventional because it’s the top-down and results-first approach designed for software engineers.
Please, feel free to make any contributions you feel will make it better.
Table of Contents
- What is it?
- Why use it?
- How to use it
- Follow me
- Don’t feel you aren’t smart enough
- About Video Resources
- Prerequisite Knowledge
- The Daily Plan
- Machine learning overview
- Machine learning mastery
- Machine learning is fun
- Inky Machine Learning
- Machine learning: an in-depth, non-technical guide
- Stories and experiences
- Machine Learning Algorithms
- Beginner Books
- Practical Books
- Kaggle knowledge competitions
- Video Series
- Becoming an Open Source Contributor
- Interview Questions
- My admired companies
Top DSC Resources
- Article: What is Data Science? 24 Fundamental Articles Answering This Question
- Article: Hitchhiker’s Guide to Data Science, Machine Learning, R, Python
- Tutorial: Data Science Cheat Sheet
- Tutorial: How to Become a Data Scientist – On Your Own
- Categories: Data Science – Machine Learning – AI – IoT – Deep Learning
- Tools: Hadoop – DataViZ – Python – R – SQL – Excel
- Techniques: Clustering – Regression – SVM – Neural Nets – Ensembles – Decision Trees
- Links: Cheat Sheets – Books – Events – Webinars – Tutorials – Training – News – Jobs
- Links: Announcements – Salary Surveys – Data Sets – Certification – RSS Feeds – About Us
- Newsletter: Sign-up – Past Editions – Members-Only Section – Content Search – For Bloggers
- DSC on: Ning – Twitter – LinkedIn – Facebook – GooglePlus