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Trees, SVM and Unsupervised Learning
  • Level Professional
  • المدة 13 ساعات hours
  • الطبع بواسطة University of Colorado Boulder
  • Offered by

عن

"Trees, SVM and Unsupervised Learning" is designed to provide working professionals with a solid foundation in support vector machines, neural networks, decision trees, and XG boost. Through in-depth instruction and practical hands-on experience, you will learn how to build powerful predictive models using these techniques and understand the advantages and disadvantages of each. The course will also cover how and when to apply them to different scenarios, including binary classification and K > 2 classes. Additionally, you will gain valuable experience in generating data representations through PCA and clustering. With a focus on practical, real-world applications, this course is a valuable asset for anyone looking to upskill or move into the field of data science. This course can be taken for academic credit as part of CU Boulder’s Master of Science in Data Science (MS-DS) degree offered on the Coursera platform. The MS-DS is an interdisciplinary degree that brings together faculty from CU Boulder’s departments of Applied Mathematics, Computer Science, Information Science, and others. With performance-based admissions and no application process, the MS-DS is ideal for individuals with a broad range of undergraduate education and/or professional experience in computer science, information science, mathematics, and statistics. Learn more about the MS-DS program at https://www.coursera.org/degrees/master-of-science-data-science-boulder.

الوحدات

Course Introduction

    • 1 Videos
    • 2 Readings
    • 1 Discussion
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1 Discussions

  • Introduce Yourself!

1 Videos

  • Course 3 Introduction

2 Readings

  • Earn Academic Credit for your Work!
  • Course Support

Introduction to SVMs

    • 4 Videos
    • 1 Readings
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4 Videos

  • Support Vector Machines: Part 1
  • Support Vector Machines: Part 2
  • Support Vector Machines: Part 3
  • Support Vector Machines: Part 4

1 Readings

  • Support Vector Machines

Assignments

    • 1 Lab
    • 1 Programming
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1 Programming

  • SVMs Assignment

1 Labs

  • SVMs Practice Lab

Neural Networks

    • 5 Videos
    • 1 Readings
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5 Videos

  • Neural Networks: Part 1
  • Neural Networks: Part 2
  • Neural Networks: Part 3
  • Neural Networks: Part 4
  • Neural Networks And Its Application To Unsupervised Learning ​​

1 Readings

  • Neural Networks

Assignments

    • 1 Programming
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1 Programming

  • Neural Networks Lab and Assignment

Introduction

    • 1 Videos
    • 1 Readings
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1 Videos

  • Decision Trees

1 Readings

  • Decision Trees and Bagging

Assignments

    • 1 Lab
    • 1 Programming
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1 Programming

  • Decision Trees Assignment

1 Labs

  • Decision Trees Walkthrough
Osita Onyejekwe
Instructor

Osita Onyejekwe