Machine Learning Box Set: 2 Books in 1

De: John Slavio

Narrado por: Russell Archey

Duración: 3 h y 38 m

Resumen del Editor

Machine Learning Box Set (2 Books in 1)

Book 1: Machine Learning This book is an introduction to basic machine learning and artificial intelligence. It gives you a list of applications, and also a few examples of the different types of machine learning.

Here's a preview of what you'll learn:

• Introduction to machine learning
• Different applications of machine learning
• Introduction to statistics for machine learning
• Supervised learning
• Unsupervised learning
• Reinforced learning
• Conclusion

Book 2: Neural Networks

Neural networks are used to model complex patterns for prediction and simulation. It uses the processing pattern used by brain neurons to achieve this. Neural Networks are good at processing complex, non-linear relationships and are used in forecasting, image processing, and character recognition.

Here's what you'll learn:

• What are artificial neural networks?
• Fundamentals of neural networks
• Activation paradigms
• Learning paradigms
• Multilayer perceptron
• Practical application - text recognition
• Practical application - image processing
• Problems with neural networks

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©2018 Kumar (P)2018 Kumar

Great book - detailed and practical.

This is the best book I've seen for professional software engineers to bootstrap themselves into Data Science, Machine Learning and (with the 2nd ed) Deep Learning. It makes heavy use of the scikit-learn library; and the latter chapters give an excellent high-level overview of TensorFlow. Books in this space can often feel either too basic or too academic. Not this one -- for me it hits the sweet spot of explaining and doing.

Clear and concise

This is the best machine learning book. The author breaks things done into simple easy to understand components. I now have a better understanding of what the ML engineers are discussing.

One great introductory.

I was able to understand the importance of using machine learning algorithms with this piece. One great introductory to start with. Every reader who’s looking forward to studying ML should grab this.

very pleased with this book

The book is an introduction to machine learning techniques which covers many of the topics without going into any detailed explanations. The focus is on how to use and understand ML rather than the math behind the algorithms.

Great job

Gives a great introduction while instigating your curiosity to explore and learn more. Love it. Would request the author to write a sequel.

Practical information

Really informative! This is a great resource for anyone looking to gain conceptual aspects of data science as well as some practical, production-ready techniques. Highly recommend.

Nice Audiobook

Clear self-contained chapters with to the point concise explanations. It covers a vast majority of different techniques, and trying to present the ideas and intuitions why this method works or how this method is an implementation of a simpler idea.

Practical information!!!

I take the courage to dive into this book. It gives me a lot of great information I never believed I can understand them. The book covers all the important topics on deep learning and it provides a lot of code examples. I am extremely happy with it.

Speeds up my learning.

Helps readers speed up with machine learning. Every data scientist would recommend this with its accurate and updated details. It’s even delivered in a fascinating way, leaving no room for dull moments.

Pleased with this book.

I learned the basic elements of this subject the fast and proper way. Kumar indeed knows how to please his readers. From the basics to algorithmic paradigms, the author has presented them in a principled way. I’m pretty glad I didn’t doubt this book when I set my eyes on it.