SangeetM/Machine-Learning-University

A set of notes & Courses which I assembled together as part of the curriculum to become a Machine Learning Engineer.

Machine Learning University

What is it?

This is my multi-month study plan for going from student developer to Machine Learning Engineer.

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Basic Programming Skills:

• CS046 - Intro to Java Programming
• UD036 - Programming foundation with Python

Mathematical Background:

• ST101 - Intro to statistics
• UD953 - Linear Algebra Refresher Course
• UD827 - Intro to Descriptive Statistics
• UD201 - Intro to Inferential Statistics

Important Mathematical Cheat Sheets:

• Linear Algebra
• Calculus
• Statistics

Major Curriculum:

• UD170 - Intro to data analysis
• UD651 - Data Analysis with R by Facebook
• UD359 - Intro to Data Science
• UD120 - Intro to Machine Learning
• CS271 - Intro to Artificial Intelligence
• UD262 - Machine Learning
• UD741 - Unsupervised Learning
• UD600 - Reinforcement Learning
• UD919 - Model Building and Validation
• UD730 - Deep Learning by Google

ML Nanodegree Project Support Courses:

• Course 1
• Course 2
• Course 3
• Course 4

Additional Courses:

• Ud032 - Data Wrangling with MongoDB
• UD436 - Computer Networking
• UD197 - Intro to Relational Database
• UD923 - Introduction to Operating Systems

Mathematics for Absolute Beginners:

• Khan Academy

More Learning Resources:

• The Mathematics for Machine Learning by IBM
• Deep Learning by Ian GoodFellow

Is it Done?

No it is not yet reached it's state of maturity. I will be adding more learning materials throughout my journey. So stay tuned.