Essentials of Machine Learning

Max Schallwig, Power through programming

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10 Lessons (1h 59m)
    • 1. Essentials Of Machine Learning

      5:11
    • 2. Essential Terms Part 1

      16:21
    • 3. Essential Terms Part 2

      8:10
    • 4. Essential Terms Part 3

      15:17
    • 5. Data Preparation Part 1

      11:24
    • 6. Data Preparation Part 2

      12:10
    • 7. Classification Algorithms Part 1

      10:41
    • 8. Classification Algorithms Part 2

      10:38
    • 9. Regression Algorithms

      13:58
    • 10. Optimization Techniques

      14:58

About This Class

Machine learning is becoming a very popular and in-demand field, with a lot of active research and new developments coming in constantly.

If you want to get a better understanding of what machine learning is all about, without having to dive super deep into all the technical details, then this course if for you.

My goal is to give you a more clear and intuitive understanding of machine learning. 

This class is focused on getting you a more complete understanding, especially about the different techniques that are used to make algorithms more accurate and learn faster, as well as the different types of ways machine learning can be used.

This course is not made to teach you about how to implement many different machine algorithms in code, but rather to give you a good understanding of the topic as a whole and the different parts that go into

  • Getting and preparing data
  • Visualizing how some machine learning algorithms some problems
  • How to evaluate the results of a machine learning algorithms
  • How to go about making your algorithm learn faster