dharani211/machine-learning-3

Resolving Python with Data Science

About

This repository contains learning materials that will help you understand how to compute different types of Mathematical Equations to varying types of data.

Requirements

Same as seen in this github repo

Instructions

Download the Materials

To download the materials, you have three options:

1. Fork the repository to your GitHub account.

   • Later, you must clone the repository in your terminal.
   • Make sure you change USERNAME to your actual username:

     git clone https://github.com/USERNAME/machine-learning

   • For example, since my username is jsulopz, I should execute the following in the terminal:

     git clone https://github.com/jsulopz/machine-learning

2. Directly clone the repository, without forking it. If you don't fork the repository, you won't be able to upload the resolution of the exercises for potential job interviewers to see what you are capable of.

   git clone https://github.com/jsulopz/machine-learning

3. Download the materials as a zip folder.

Interacting with the Materials

1. Each folder represents a chapter.
2. Each chapter may contain up to 6 types of files:
   1. x_topic-y_**syllabus**.ipynb to understand the practical use case and the concepts you will uncover as you interact with the chapter.
   2. x_topic-y_**session_blank**.ipynb to develop the solutions of the session notebook.
   3. x_topic-y_**session_solution**.ipynb to uncover the solutions of the session notebook.
   4. x_topic-y_**practice_blank**.ipynb to develop the solutions of the practice notebook.
   5. x_topic-y_**practice_solution**.ipynb to uncover the solutions of the practice notebook.
   6. instructions.md to follow a series of steps to complete the chapter.