Machine Learning Roadmap

In Machine Learning, we use data and algorithms to build intelligent systems. In the next ten years, you will explore many new high-paying jobs that require you to know about Machine Learning. So the time you will spend today learning Machine Learning will never go waste. So, if you are looking for a complete roadmap you can follow for learning Machine Learning, this article is for you. In this article, I will take you through a Machine Learning Roadmap with all the learning resources you can follow to be an expert in Machine Learning.

Machine Learning Roadmap

Here’s a complete roadmap you can follow to learn Machine Learning step by step:

  1. Explore the fundamentals of Machine Learning
  2. Learn Python
  3. Learn Necessary Python Libraries
  4. Learn & Implement Machine Learning Algorithms
  5. Learn & Implement Neural Networks
  6. Work on Projects

Now let’s explore each step of the roadmap one by one.

Step 1: Explore the Fundamentals of Machine Learning

When we start learning to drive a car, we are introduced to its components, types, and rules to drive a car. In the same way, you need to go through all the fundamentals of Machine Learning to know what you are about to learn and how much you have to learn.

Below are some of the best resources to learn the fundamentals of Machine Learning:

  1. Understanding Machine Learning: From Theory to Algorithms (Book)
  2. Mathematics for Machine Learning (Book)
  3. Machine Learning Crash Course by Google Developers

Step 2: Learn Python

The next step in the Machine Learning roadmap is to learn Python. Python is one of the best programming languages for numerical calculations and working with data. You will find many opportunities in the Machine Learning field as a Python developer.

Below are some of the best resources to learn Python:

  1. Complete Python Course by Tech with Tim (YouTube)
  2. Python Course by Freecodecamp (YouTube)

Step 3: Learn Necessary Python Libraries

After learning Python, the next step in the Machine Learning roadmap is learning the necessary Python libraries you need while working with data and implementing Machine Learning using Python.

Below are the necessary Python libraries you need to learn for Machine Learning:

  1. NumPy
  2. Pandas
  3. Matplotlib
  4. Scikit-learn
  5. Keras
  6. Tensorflow

Step 4: Learn and Implement Machine Learning Algorithms

The next step in the Machine Learning roadmap is to learn Machine Learning algorithms and their implementation using Python.

Below are some of the most important Machine Learning algorithms you need to learn:

  1. Linear Regression
  2. Logistic Regression
  3. Passive Aggressive
  4. Naive Bayes
  5. Support Vector Machines
  6. Decision Trees
  7. K-Nearest Neighbors
  8. Random Forests
  9. K-Means
  10. DBSCAN
  11. PCA
  12. Kernel PCA
  13. t-SNE
  14. Apriori

You can learn about all these algorithms and their implementation using Python from the resources mentioned below:

  1. Mastering Machine Learning Algorithms
  2. Machine Learning Algorithms & Models

Step 5: Learn and Implement Neural Networks

The next step in the Machine Learning roadmap is to learn neural network architectures and their implementation using Python.

Below are some of the most important neural network architectures you need to learn:

  1. Perceptron
  2. Artificial neural networks
  3. Multilayer Perceptron
  4. Radial networks
  5. Convolutional neural networks
  6. Recurrent neural networks
  7. Long-Short-Term Memory

Below are some resources you can follow to learn about all these neural network architectures:

  1. Introduction to Deep Learning (YouTube)
  2. Deep Learning with Python (Book)
  3. Deep Learning for Beginners (Book)
  4. Machine Learning Foundations (YouTube)

Step 6: Work on Projects

The next step in the Machine Learning roadmap is working on projects to implement what you learned. As a beginner, work on projects meant for beginners. Below are some Machine Learning project ideas for beginners:

  1. Iris Flower Classification
  2. California House Price Prediction
  3. Stock Price Prediction
  4. Customer Segmentation

All the project ideas mentioned above are popular in the Machine Learning community, so you will easily find many resources on the internet to work on these projects as a beginner.

After working on beginner-level projects, you can explore more Data Science and Machine Learning projects from here.

Summary

So below is a complete roadmap you can follow to learn Machine Learning step by step:

  1. Explore the fundamentals of Machine Learning
  2. Learn Python
  3. Learn Necessary Python Libraries
  4. Learn & Implement Machine Learning Algorithms
  5. Learn & Implement Neural Networks
  6. Work on Projects

I hope you liked this article on a Machine Learning roadmap with learning resources. Feel free to ask valuable questions in the comments section below.

Aman Kharwal
Aman Kharwal

I'm a writer and data scientist on a mission to educate others about the incredible power of data📈.

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