- #1

gillouche

Gold Member

- 25

- 7

Hi everyone,

I am a software developer (bachelor's degree in Europe, different than a bachelor's degree in the US I believe) and I don't have a strong math/physics background but I am willing to learn.

For a few years now, I have been really interested in machine learning but until now, I only read blog posts and examples in python. Now, I would really like to learn the maths and get the intuition behind ML so I need resources adapted to my maths background.

I haven't started working on Multivariable calculus, linear algebra and differential equations on Khan Academy yet so I have a lot of work to do. I also worked on paul's online notes (http://tutorial.math.lamar.edu/) except Calculus III and diffeq.

I read online that the following maths are required to properly learn machine learning concepts

1) probability and statistics

I have Mathematical Methods in the Physical Sciences from Mary Boas, I don't know if that's enough.

any online resources, books (free or not) that you would recommend ?

2) Linear algebra

I have two books from Serge Lang :

Introduction to Linear Algebra Undergraduate Texts in Mathematics

Linear Algebra Undergraduate Texts in Mathematics

I plan to complete that with Khan Academy and his MIT lectures. I guess that for linear algebra, I will be fine once I finished working on these resources.

3) Calculus / multivariable calculus ?

I learned with Khan Academy / Patrick JMT but I never worked with other resources. I guess I should review that topic with a more formal book. Any advice ?

4) Optimization

I don't have any resources treating this subject.

Thank you very much.

I am a software developer (bachelor's degree in Europe, different than a bachelor's degree in the US I believe) and I don't have a strong math/physics background but I am willing to learn.

For a few years now, I have been really interested in machine learning but until now, I only read blog posts and examples in python. Now, I would really like to learn the maths and get the intuition behind ML so I need resources adapted to my maths background.

I haven't started working on Multivariable calculus, linear algebra and differential equations on Khan Academy yet so I have a lot of work to do. I also worked on paul's online notes (http://tutorial.math.lamar.edu/) except Calculus III and diffeq.

I read online that the following maths are required to properly learn machine learning concepts

1) probability and statistics

I have Mathematical Methods in the Physical Sciences from Mary Boas, I don't know if that's enough.

any online resources, books (free or not) that you would recommend ?

2) Linear algebra

I have two books from Serge Lang :

Introduction to Linear Algebra Undergraduate Texts in Mathematics

Linear Algebra Undergraduate Texts in Mathematics

I plan to complete that with Khan Academy and his MIT lectures. I guess that for linear algebra, I will be fine once I finished working on these resources.

3) Calculus / multivariable calculus ?

I learned with Khan Academy / Patrick JMT but I never worked with other resources. I guess I should review that topic with a more formal book. Any advice ?

4) Optimization

I don't have any resources treating this subject.

Thank you very much.

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