Machine Learning for Beginners

Machine Learning for Beginners

This beginner-level machine learning course covers the fundamental topics for coders aspiring to become ML engineers.

Beginner

18 Lessons

4h

Certificate of Completion

This beginner-level machine learning course covers the fundamental topics for coders aspiring to become ML engineers.

AI-POWERED

Code Feedback
Explanations

AI-POWERED

Code Feedback
Explanations

This course includes

37 Playgrounds
5 Quizzes

This course includes

37 Playgrounds
5 Quizzes

Course Overview

This course explains machine learning for absolute beginners by building a visual understanding of the underlying concepts. It covers some foundational mathematics behind the machine learning models and then guides you in coding for models to solve real-world machine learning problems. You’ll begin by understanding the limitations of traditional coding techniques in solving machine learning problems. Next, you’ll get familiar with the machine learning process. Then, you’ll build your first machine learning...Show More

What You'll Learn

An understanding of the fundamentals of machine learning

The ability to build the model of a simple perceptron from scratch

Hands-on experience building a multilayer neural network from single neurons

Hands-on experience solving machine learning problems such as classification, regression, and clustering using Python and sklearn

What You'll Learn

An understanding of the fundamentals of machine learning

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Course Content

1.

The Machine Learning Problem

There are problems that typical programming techniques can’t solve. This chapter introduces those problems and the machine learning process for solving them.
2.

The Machine Learning Process

This chapter establishes the mathematical and visual understanding of each phase of the ML process and codes each step from scratch.
3.

From a Single Neuron to Artificial Neural Networks

This chapter continues with the machine learning journey by unfolding the model of artificial neural networks, explaining what the hidden layers do and how to train them.
4.

Code for Machine Learning Using scikit-learn

This chapter introduces other classes of machine learning problems, e.g., unsupervised, reinforcement learning, regression, and clustering with scikit-learn.
5.

Concluding Thoughts

This concluding chapter summarizes what we learned and explores what lies beyond the bounds of ML.

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Souvik Kundu

Front-end Developer

Eric Downs

Musician/Entrepeneur

Anthony Walker

@_webarchitect_

Emma Bostian 🐞

@EmmaBostian

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