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Here we are going to learn Mathematics for Data Science. Mathematics sucks!! I don't wanna learn it and atleast from this non- audio video nah man! Well you can leave.
The topics which we are going to cover are:
1. Prerequisites
2. Set theory
3. Geometry - Straight lines, quadratic equations, Polynomials
4. Calculus
5. Lots of calculus
6. Matrices and Vectorss
All of it in the span of 6-8 months. But it is gonna be hectic. Not for you for my fingers Man.
Mathematics starts here,
1. Prerequisites:
a. Induction Reasoning:
Induction reasoning in layman's term is Making conclusions, generalisations on the basis of what is presented to you, given to you. Like you choose yellow Mangoes and not green ones. Wonder why?
Coz. You have seen it from your childhood green are always bad with few, very few exceptions.
So, we can/may write our understanding as follows:
Making generalisations on the basis of given information. Where, generalisations refers to identification of formulae, functions, or patterns.
Let's go onto solve some problems:
Problem 1: 1, 3, 5, 7, _, _, _
Well 1, 3, 5, and & are given and we are asked to find next three numbers. By giving it a thought we cam to the conclusion that these are odd numbers and therefore the next three numbers are going to be 9, 11, 13. And same pattern can be used for any particular n^th term.
Write, now we have fair understanding of what is this Induction Reasoning.
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