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How Machine Learning Works

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Paolo Perrotta

2:22:43

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  • 01 - Course Overview.mp4
    02:00
  • 02 - Getting to Know Machine Learning.mp4
    01:45
  • 03 - Programming vs. Machine Learning.mp4
    02:34
  • 04 - Supervised Learning.mp4
    03:04
  • 05 - Approximating a Function.mp4
    04:04
  • 06 - Tackling a Machine Learning Problem.mp4
    03:01
  • 07 - Making Sense of Our Data.mp4
    04:18
  • 08 - Understanding Linear Regression.mp4
    02:59
  • 09 - Implementing Prediction.mp4
    02:50
  • 10 - Understanding the Loss.mp4
    04:36
  • 11 - Implementing the Training Algorithm.mp4
    04:56
  • 12 - Running the Code.mp4
    02:38
  • 13 - Our Algorithm Doesnt Cut It.mp4
    02:39
  • 14 - Understanding Gradient Descent.mp4
    06:10
  • 15 - Descending the Gradient in Three Dimensions.mp4
    02:35
  • 16 - Calculating the Gradient.mp4
    02:13
  • 17 - Implementing Gradient Descent.mp4
    03:54
  • 18 - Dealing with a Complicated World.mp4
    04:39
  • 19 - Tricking Away the Bias.mp4
    01:36
  • 20 - Switching to Matrices.mp4
    04:09
  • 21 - Shaping Data.mp4
    05:46
  • 22 - Upgrading the Loss.mp4
    04:04
  • 23 - Running Multiple Regression.mp4
    04:12
  • 24 - Getting to Know Classification.mp4
    03:48
  • 25 - From Regression to Classification.mp4
    03:24
  • 26 - Introducing the Log Loss.mp4
    04:29
  • 27 - Testing the Classifier.mp4
    03:30
  • 28 - Introducing MNIST.mp4
    03:09
  • 29 - Understanding the Test Set.mp4
    03:26
  • 30 - Preparing the Images.mp4
    04:07
  • 31 - Preparing the Labels.mp4
    03:14
  • 32 - Recognizing a Digit.mp4
    04:34
  • 33 - Planning for Multiple Classes.mp4
    02:39
  • 34 - Encoding the Labels.mp4
    03:41
  • 35 - Updating the Weights.mp4
    02:46
  • 36 - Updating Prediction.mp4
    03:25
  • 37 - Running the Final Test.mp4
    03:08
  • 38 - From the Basics to the Perceptron.mp4
    03:39
  • 39 - Understanding the Perceptrons Limitations.mp4
    04:03
  • 40 - The Story So Far.mp4
    04:59
  • Description


    Machine learning is amazing… and intimidating. How can computers do magical things like understand images or text? This training for programmers will dispel the magic and help you to build your own computer vision program, starting from scratch.

    What You'll Learn?


      Machine learning is fascinating, but those math-heavy tutorials can be intimidating, even for a programmer. In this course, How Machine Learning Works, you’ll learn the basics of machine learning from code. First, you will have a look at supervised learning, and you'll quickly move to coding your first learning program, and see how to improve that program line by line. Then, you'll discover how to improve that program line by line. Finally, you'll see how to write this program by yourself, without resorting to obscure machine learning libraries. By the end of the course, you'll have a working computer vision program that recognizes handwritten characters, and you'll have practical knowledge of the foundational ideas of machine learning.

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    Paolo Perrotta
    Paolo Perrotta
    Instructor's Courses
    Paolo Perrotta is the author of "Programming Machine Learning" and "Metaprogramming Ruby". He has hundreds of articles, conference speeches and training deliveries under his belt. He developed software in domains ranging from automotive to healthcare, large-scale web sites, and computer games.
    Pluralsight, LLC is an American privately held online education company that offers a variety of video training courses for software developers, IT administrators, and creative professionals through its website. Founded in 2004 by Aaron Skonnard, Keith Brown, Fritz Onion, and Bill Williams, the company has its headquarters in Farmington, Utah. As of July 2018, it uses more than 1,400 subject-matter experts as authors, and offers more than 7,000 courses in its catalog. Since first moving its courses online in 2007, the company has expanded, developing a full enterprise platform, and adding skills assessment modules.
    • language english
    • Training sessions 40
    • duration 2:22:43
    • level preliminary
    • Release Date 2023/10/15