How to learn machine learning from scratch

Machine learning is a rapidly growing field with a wide range of applications, from self-driving cars to spam filtering to medical diagnosis. As a result, there is a high demand for skilled machine learning professionals.

If you’re interested in learning machine learning from scratch, there are a few things you need to do to get started.

1. Build a foundation in math and statistics

Machine learning is a mathematical field, so it’s important to have a strong foundation in math and statistics. This includes topics like calculus, linear algebra, and probability.

There are many resources available to help you learn these topics, including online courses, textbooks, and tutorials.

Here are a few specific resources you can check out:

Math for Machine Learning by Sebastian Raschka
Statistics for Machine Learning by Galit Shmueli
Linear Algebra for Machine Learning by Yoshua Bengio

2. Choose a programming language

Most machine learning libraries are written in Python, so it’s a good idea to learn this language. However, you can also use other languages like R and Julia.

There are many resources available to help you learn Python, including online courses, textbooks, and tutorials.

Here are a few specific resources you can check out:

Python Crash Course by Eric Matthes
A Byte of Python by Swaroop Puranik
Python for Data Analysis by Wes McKinney

3. Learn the basics of machine learning

Once you have a foundation in math and programming, you can start learning the basics of machine learning. This includes topics like supervised learning, unsupervised learning, and reinforcement learning.

There are many resources available to help you learn the basics of machine learning, including online courses, textbooks, and tutorials.

Here are a few specific resources you can check out:

Machine Learning: A Probabilistic Perspective by Kevin P. Murphy
Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow by Aurélien Géron
Machine Learning for Beginners by Andrew Ng

4. Get hands-on experience

The best way to learn machine learning is by doing. Start working on machine learning projects, even if they’re small.

There are many resources available to help you find machine learning projects, including online platforms like Kaggle and GitHub.

Here are a few ideas for machine learning projects you can work on:

Build a spam filter
Predict customer churn
Recommend products to customers
Classify images
Build a chatbot

5. Join a community of machine learners

Learning machine learning can be challenging, so it’s helpful to join a community of machine learners. This can be done online or in person.

There are many online machine learning communities, such as the r/MachineLearning subreddit and the TensorFlow Discord server. There are also many in-person machine learning meetups and conferences.

Tips for learning machine learning

Here are a few additional tips for learning machine learning:

Start with the basics. Don’t try to learn everything about machine learning at once. Start with the basics and then gradually build your knowledge.
Don’t be afraid to ask for help. There are many people who are willing to help you learn machine learning. If you’re stuck on something, don’t be afraid to ask for help on a forum or from a friend or colleague.
Be patient. Learning machine learning takes time and effort. Don’t get discouraged if you don’t understand something right away. Just keep practicing and you’ll eventually get it.

Conclusion

Learning machine learning from scratch can be challenging, but it’s also very rewarding. By following the tips above, you can start your journey to becoming a skilled machine learning professional.