Understand which algorithms to use in a given context with the help of this exciting video-based guide
Learn about perceptrons and see how they are used to build neural networks
Stuck while making sense of images, text, speech, and real estate? This guide will come to your rescue, showing you how to perform machine learning for each one of these using various techniques
Machine learning is increasingly pervasive in the modern data-driven world. It is used extensively across many fields such as search engines, robotics, self-driving cars, and more.
With this course, you will learn how to perform various machine learning tasks in different environments. Well start by exploring a range of real-life scenarios where machine learning can be used, and look at various building blocks. Throughout the course, youll use a wide variety of machine learning algorithms to solve real-world problems and use Python to implement these algorithms.
Youll discover how to deal with various types of data and explore the differences between machine learning paradigms such as supervised and unsupervised learning. We also cover a range of regression techniques, classification algorithms, predictive modelling, data visualization techniques, recommendation engines, and more with the help of real-world examples.
- 1,082.7 MB
- Release Date:
- Jason Stafford
Safe to Download