The Machine Learning Algorithms A-Z

with Jeff Li and Ken Jee

Learn the intuition behind the most popular ML algorithms, understand the pros and cons of each, and choose the best one for the problems you need to solve.

5 hours 189 lessons
Start course
189 High Quality Lessons
0 Practical Tasks
5 Hours of Content
Certificate of Achievement

Course Overview

Looking to break into machine learning? Need to review the ins and outs of each algorithm? Preparing for an interview? Curious to see how these algorithms are applied to business? As ML practitioners, the true value of ML is not in memorizing complicated formulas. It’s not using the latest, greatest deep learning architecture. It’s knowing when to use an algorithm and how to maximize the impact of that model. It’s knowing how to use them to solve REAL business problems. The true value of ML is not ML. It’s solving important business problems. Whether you need to build a forecasting model that forms the backbone of the ads business, builld a recommender system powering millions of purchases or build a fraud detection system that catches bad apples, this course will arm you with both the ML knowledge AND the know-how on how to apply it to your business problem. We don’t want you to leave this course just knowing ML. We want you to leave this course to leave as ML practitioners.

Topics covered

Artificial Neural Netsdecision treesGradient Boosted TreesGradient Descenthierarchical clusteringK Nearest Neighborsk-means clusteringRandom ForestSupport Vector MachinesXGBoost

What You'll Learn

You will learn the ins and outs of each algorithm and we’ll walk you through examples of the world’s biggest tech companies using these algorithms to apply to their problems. This course touches on several key aspects a practitioner needs in order to be able to aply ML to business problems:

ML Algorithms intuition
The pros and cons of different ML algorithms
When to use and when not to use ML
How the ML process works for every algorithm
Assumptions behind ML algorithms
Real-world examples on situations when specific types of ML algorithms can be used


Student feedback


310 ratings
5 stars
251 (81%)
4 stars
37 (12%)
3 stars
10 (3%)
2 stars
6 (2%)
1 star
6 (2%)
Filter by rating
  • 5 stars
  • 4 stars
  • 3 stars
  • 2 stars
  • 1 stars
  • Newest
  • Oldest
This course gives an introduction to ML algorithms. It is great to get an idea about algorithms, but not to learn in detail. One of the main drawbacks for me is that this course has no lecture notes.
A lot of meaningful and useful data here, but needs a practical application to go along with the lectures. Needs more hands on examples to solidify each topic section.
WOW, Best course present to prepare for the DS interviews. (Starters make sure you have good hold over the subject, do not just mug the content).
Thank you very much! Are you working on any classes where you combine ML tools with ChatGPT + Prompt engineering?
Same old wine in a new bottle. Nothing new from the previous version.. except the mathematical formulae.
  • 1
  • 2
  • 3
  • ...
  • 5
  • ...
  • 9
Jeff Li

“Most courses only explain the concept itself, and they’re done. Not only do we teach you the concept, but we also lay out its pros and cons and when you should use the concept to solidify your intuition. ”

Jeff Li

Works at Large music streaming platform

The Machine Learning Algorithms A-Z

with Jeff Li and Ken Jee

Start Course