First things first you need to learn basic fundamentals of python programming language.
The next step is to learn Scikit-learn, which is a modern machine learning library written in Python.
I consider Sckit-learn to be the best for beginners and most of the Machine learning algorithms are pre-written for you.
Start learning LINEAR ALGEBRA now!
You should learn Linear Algebra if you wish to master Machine Learning and become a pro!
This is essential if you want to tune your ML models with maximum flexibility.
Tips to learn
You can learn Scikit-learn & Linear Algebra simeultaneously!
This will save you time and can help you to keep your enthusiasm and motivation up.
*Learn Probability & Statistics
*
Having a basic understanding of probability and statistics is important when it comes to mastering Machine Learning.
Learn Core ML Algorithms
In order to get an idea of how these ML algorithms work look into:
• Gradient Descent
Slope
• Supervised vs Unsupervised learning
• Reinforcement Learning
• Basic Linear Regression
• Working with all such similar models
• Clustering
Learn Python Libraries
• Learn Numpy
• Learn Pandas
• All this will be helpful to debug the python/sklearn code.
Learn Deployment
To host your machine learning models with a powerful backend, you will need to learn frameworks like Django or Flask.
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