Introduction to Machine Learning (Self-Paced Tutorial)

Details

The Introduction to Machine Learning course will allow you to learn about specific techniques used in supervised, unsupervised, and semi-supervised learning, including which applications each type of machine learning is best suited for and the type of training data each requires.

You will discover how to differentiate offline and online training and predictions, automated machine learning, and how the cloud environment affects machine learning functions. Additionally, you will explore some of the most significant areas in the field of machine learning research.

Enrollment Options:

Self-Paced
3 Months Access Course Code: T14287
No Instructor, Start Anytime

$129.99

USD

Enroll before 28th February and get high quality lamination on your hardcopy certificate absolutely free! Use your certificate to your advantage by showing your certified credentials to prospective employers and recruiters.

Syllabus

  1. Introduction to Machine Learning
  2. Which Problems Can Machine Learning Solve?
  3. The Machine Learning Pipeline
  4. Working with Data
  5. Supervised Learning: Regression
  6. Supervised Learning: Classification
  7. Ensemble Methods
  8. Unsupervised Learning
  9. Semi-Supervised Learning
  10. Reinforcement Learning
  11. Building and Deploying Machine Learning Apps
  12. Beyond Machine Learning

Requirements

Hardware Requirements:

  • This course can be taken on either a PC or Mac.

Software Requirements:

  • PC: Windows 8 or newer.
  • Mac: OS X Snow Leopard 10.6 or later.
  • Browser: The latest version of Google Chrome or Mozilla Firefox are preferred. Microsoft Edge and Safari are also compatible.

Other:

  • Email capabilities and access to a personal email account.

Prerequisites

There are no prerequisites to take this course.

Reviews

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