In this article I will continue with the Story of Logistic Regression, if you have not read the previous article, here is the link

Let me make things clear and simple, even in this article i won’t be able to complete Logistic Regression because its a broad topic and we are covering it in detail so it is better to plan what we gonna cover in this article.

We will be covering:

1. Probablistic approach of sigma function.
2. Optimization Theory.
3. We will derive optimization problem of LR by geometry.
4. WEIGHT VECTOR
5. We will deal with Overfitting problem.
6. We will see L1 and L2 regularization in detail.

So lets get started,

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