**Fundamental Math Concepts for Data Science / ML / AI**

Submitted by
**Vishal (@vishalgokhale)**
on Friday, 27 October 2017

*videocam_off*

Section: Workshop Technical level: Beginner

### Abstract

Many beginners intrigued by Data Science/ML/AI behold it in the awe and fear reserved for a hairy monster,

A lot of really interested, good prorammers seem to maintain distance from it because they are just plain scared of the math.

The workshop will be a refresher of the basic concepts and does not assume any prior knowledge greater than addition, subtraction, multiplication and division.

### Outline

Concepts Covered:

Indices and Logarithms,

Functions,

Polynomials, shapes of polynomial functions,

Binomial expansion,

Combinatrics,

Probability,

Calculus concepts (Derivatives, Integration) and its application in gradient descent,

PDF/CDF, concept and examples - Binomial/Normal distribution ....

### Requirements

Knowing how to do addition, subtraction, multiplication and division.

Internet: We’ll use online tools for graphing and seeking help from our beautiful friend- google

Pen, paper and some grit to keep writing as existential Xs stareback at you asking “Who am I? Why am I here?”

### Speaker bio

I am a programmer with an odd love for maths. I enjoy simplifying heavy math protein into more absorbable amino acids, only to be assimilated into plump biceps of confidence, to be flexed when the situation demands.

I want to infect people with the addictive epiphanies from solving math problems.

and btw, I have been working as a programmer on Data Science projects for the last 6+ years and as a programmer for last 13+ years.