Everything you need to know about the math for machine learning as a beginner.

Before diving into the math, I suggest first having solid programming skills.

For example

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In Python, these are the concepts which you must know:

- Object oriented programming in Python : Classes, Objects, Methods
- List slicing
- String formatting
- Dictionaries & Tuples
- Basic terminal commands
- Exception handling

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If you want to learn python, these courses are freecodecamp could be of help to you.

Basics: youtube .com/watch?v=rfscVS0vtbw
Intermediate :youtube .com/watch?v=HGOBQPFzWKo

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You need to have really strong fundamentals in programming, because machine learning involves a lot of it.

It is 100% compulsory.

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Another question that I get asked quite often is when should you start learning the math for machine learning?

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Math for machine learning should come after you have worked on some projects, doesn't have to a complex one at all, but one that gives you a taste of how machine learning works in the real world.

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Here's how I do it, I look at the math when I have a need for it.

For instance I was recently competing in a kaggle challenge.

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I was brainstorming about which activation function to use in a part of my neural net, I looked up the math behind each activation function and this helped me to choose the right one.

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The topics of math you'll have to focus on
- Linear Algebra
- Calculus
- Trigonometry
- Algebra
- Statistics
- Probability

Now here are the math resources and a brief description about them.

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Neural Networks
> A series of videos that go over how neural networks work with approach visual, must watch

youtube. com/watch?v=aircAruvnKk&list=PLZHQObOWTQDNU6R1_67000Dx_ZCJB-3pi

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Seeing Theory
> This website gives you an interactive to learn statistics and probability

seeing-theory. brown. edu/basic-probability/index.html

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Gilbert Strang lectures on Linear Algebra (MIT)
> They're 15 years old but still 100% relevant today!
Despite the fact these lectures are for freshman college students ,I found it very easy to follow.

youtube. com/playlist?list=PL49CF3715CB9EF31D

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Essence of Linear Algebra
> A beautifully crafted set of videos which teach you linear algebra through visualisations in an easy to digest manner

youtube. com/watch?v=fNk_zzaMoSs&list=PLZHQObOWTQDPD3MizzM2xVFitgF8hE_ab

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Khan Academy
>The resource you must refer to when you forget something or want to revise a topic.

khanacademy. org/math

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Essence of calculus
> A beautiful series on calculus, makes everything seem super simple

youtube. com/watch?v=WUvTyaaNkzM&list=PL0-GT3co4r2wlh6UHTUeQsrf3mlS2lk6x

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The math for Machine learning e-book
> This is a book aimed for someone who knows a decent amount of high school math like trignometry, calculus etc.

I suggest reading this after having the fundamentals down on khan academy.

mml-book. github .io

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