Instead of using hard-coded rules for performing something, artificial intelligence (AI) and machine learning (ML) prepare the machines to learn things from data to decipher the complex patterns automatically and then use it for building multiple use cases. If you too want to make applications and solve complex problems using AI and ML, then this course will help you to get started with the basics.
The course starts by highlighting the learning objectives and explains the rise of AI in today’s world. Next, you will be introduced to the concepts of ML. You will learn to understand ML terminologies and learn how to train a model. Towards the end, you will become familiar with the classification of ML systems, including the topics of supervised and unsupervised learning, regression, clustering, and reinforcement.
By the end of this course, you will have a fundamental knowledge of AI and ML.
All the resource for this course are available at https://github.com/PacktPublishing/Machine-Learning-for-Absolute-Beginn…
Find out why machine learning (ML) is called a black box
Get to grips with the features and labels of ML
Uncover techniques for training ML models
Find out the differences between supervised and unsupervised learning
Understand regression, clustering, and dimension reduction
* Find out how ML helps in training a model
* Discover how ML systems are classified