#datascience #machinelearning #math
Timing Breakdown
0:00 - Intro & Overview
1:53 - Statistics & Probability
4:14 - Linear Algebra
6:10 - Mathematical Optimization
8:28 - Calculus
11:05 - Specific data Science tasks & math you need to know for them
13:33 - Final Thoughts
** note: the links below are affiliate links, meaning I receive a small referral commission
FIND A SUPER COOL DATA SCIENCE MENTOR
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MY RECOMMENDED DATA SCIENCE COURSERA COURSES
Professional Data Science Certificate (IBM): [ Ссылка ]
Python for Everybody (University of Michigan): [ Ссылка ]
Machine Learning (Stanford): [ Ссылка ]
Statistics with Python (University of Michigan): [ Ссылка ]
And finally, for data people who didn’t major in computer science and are tired of getting made fun of by software engineers:
Data Structures and Algorithms (UC San Diego) - [ Ссылка ]
🍓🍍JUICY LINKS FROM VIDEO🍍🍓
Definition of statistics: [ Ссылка ]
Definition of probability: [ Ссылка ]
Statistics terms for data science summary: [ Ссылка ]
Probability terms for data science summary:
[ Ссылка ]
Definition of Linear Algebra:
[ Ссылка ]
Basic Linear algebra term definitions: [ Ссылка ]#
Mathematical Optimization Definition: [ Ссылка ]
Optimizations in machine learning: [ Ссылка ]
[ Ссылка ]
Calculus for Data Science: [ Ссылка ]
Math in deep learning: [ Ссылка ]
Experimental Design: [ Ссылка ]
Another take on the math you need for data science: [ Ссылка ]
Anotha one: [ Ссылка ]
