Experience the power of machine learning by working on nine real-world projects
About This Video
- Grasp the core concepts of machine learning (ML)
- Find out how to use neural networks in ML projects
- Learn how to build real-world projects using supervised and unsupervised learning algorithms
From self-driving cars to artificial intelligence (AI) bots, machine learning (ML) is slowly spreading its reach and making our devices smarter. If you have ever wanted to play a role in the future of technology development, then here is your chance to get started with ML. This course breaks the complex topics of ML into simple concepts that are easier to understand.
The course starts with an introduction to ML, explaining its applications in the real-world and how it is different from AI. Next, you will learn supervised and unsupervised algorithms and understand the role of neural networks in ML. Once you understand the ML algorithms, you will dive into building interesting projects to consolidate your learning. You will learn how to build a board game review prediction model, how to build a credit card fraud detection model, how to tokenize word and sentences using natural language processing), how to build an object recognition model, how to build an image quality improvement model, how to build a text classification model, how to build an image analysis model, and how to build a data compression model.
By the end of this course, you will have gained the skills to create real-world ML solutions.
Table of contents
- Title: Projects in Machine Learning: From Beginner to Professional
- Release date: February 2018
- Publisher(s): Packt Publishing
- ISBN: 9781789138245
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