Machine Learning Roadmap
This is complete end to end machine learning roadmap, whether you are a beginner or a expert in machine learning, this is comprehensive roadmap for one to ace in machine learning.
If you are a beginner then first you need to identify which type of beginner you are, there are quite a different type of beginners as follows:
- Who knows is new to programming and have no prior experience in that.
- Who knows little bit of programming like what are loops/case/if-else, done in high school but needs to revise concepts before starting
- Who are in currently studying computer science in engineering or in bachelors, but they want to start with machine learning.
- Who knows good mathematics but new to programming and machine learning
we will look into each of them and from where one should start to learn machine learning.
starting from 1st one, the one who is new to programming, don’t know anything about it, is a absolute beginner, these kind of people should start from learning python or any other programming language like c++, c, java, but python is preferred for machine learning as it has very good community support in terms of tools available to implement machine learning. one can learn python from:
Some good books to learn python are:
- Learn Python the Hard Way: 3rd Edition
- Python cookbook: Recipes for Mastering Python (3rd Edition)
- Python Crash Course
After going through how python works, basic, constructs, we recommend to do some problem solving using python. There are alot of good platforms for that. some of them are listed below:
Now comes the 2nd type of people who know what is python how it works but don’t know a great deal about programming.
They can directly jump into Problem solving using python on Leetcode or Hackerrank to brush up their concepts.
This same guide of practicing python for problem solving would be recommended to 3rd type of candidates and for 4th type of candidates, they can follow guide for 1st type of candidates.
Now you know how to code in python, write loops, if-else and basic constructs.
To learn machine learning and data science you need to learn some specific libraries in python where each library has its own importance in the field of machine learning. They are as follows:
- Numpy: used for optimised numerical computations in python.
- Pandas: used for data handling and data manipulation.
- Matplotlib: used for data visualization
- Seaborn: used for data visualization in extension with matplotlib to create enhanced visualizations.
- Probability and Statistics
- Linear Algebra
- Number Theory
- Convex Optimization