Artificial Intelligence in 3 Hours [Video]

4 (1 reviews total)
By Luka Anicin
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  1. Understanding Supervised Machine Learning

About this video

What do self-driving cars, face recognition, web search, industrial robots, missile guidance, and tumor detection have in common? They are all complex real-world problems being solved with applications of intelligence (AI). This course provides you with a broad understanding of the basic techniques for building intelligent computer systems and an understanding of how AI is applied to problems.

In this course, you will progress to advanced AI techniques and concepts, and work on real-life datasets on how training works, model evaluation and how to process their first dataset in Supervised and Unsupervised Learning. You will be introduced to neural networks, machine Learning, and Deep Learning. You will understand the concept of Artificial Intelligence and how it is applicable in the enterprise context. You will then cover the basics of machine learning relate how Deep Learning and AI fits with them.

Finally, you will see understand, Deep Reinforcement Learning and will be able to implement AI in your applications.

Style and Approach

A comprehensive course that takes you through AI in 3 hours. It is packed with step by step instructions and working examples.

Publication date:
March 2019
Publisher
Packt
Duration
3 hours 5 minutes
ISBN
9781838646196

About the Author

  • Luka Anicin

    Luka Anicin is a passionate and experienced Artificial Intelligence Engineer and he loves to share knowledge with others! In his career he had worked on many different and exciting projects where he had an opportunity to apply some of currently most advanced AI algorithms. Some project that Luka has in his portfolio: Electricity grid optimization for multiple countries, OCR for car chassis numbers, deploying chatbots for multiple customers, object detection pipeline for image search system, etc.
    He is putting his knowledge and experience into one, to create courses for people interested in Data Science.

    Browse publications by this author

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