Statistics

Calculus

Linear algebra

Statistics is also divided into two branches which are inferential and descriptive. Statistics is used in a large number to develop new algorithms and applications. This also helps to create a summary image of an industry’s process flow.

Calculus is the math branch that studies the changes and optimizes the result at the end. If you don’t have knowledge of calculus it will be difficult to find better outcomes and fix the issue.

Last but not least is linear algebra. To deal with a problem it provides fast speed. Also helps to understand the different algorithms. It can be accessed in Python using the NumPy library. With the combination with Calculus, it helps us decision-making in vectors and matrices.]]>

Welcome to the forum.

Tell me more about "sum of squared residuals in linear regression".

I used to teach this, back in the stone age, so maybe I can help.

Bob

]]>**Welcome to the forum!**

Please see the link Using and Handling Data

This can be of help.

]]>I already know some data science-related coding, and have been an intern at an entry-level startup and did some AI-related stuff and data cleaning. However, I can already feel my lack of math knowledge affecting my self-studies, as I read tutorials and come across math notations regarding equations that describe a machine-learning algorithm, etc. For example, I struggled with the following equation for calculating the sum of squared residuals in linear regression. SSR = Σᵢ(?ᵢ - ?(?ᵢ))².

So now that you get an idea of how disconnected I've been from math in the past 3 - 4 years, please point me to the topics in MathIsFun I should familiarize myself with. And also, please recommend good books considering the level of knowledge I have now.

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