Despite being one of the biggest technical leaps in AI in decades, building an understanding in deep learning doesn’t mean you need a math degree. All it takes is the right intuitive approach, and you’ll be writing your own neural networks in pure Python in no time!Grokking Deep Learning in Motion is a new course that takes you on a journey into the world of deep learning. Rather than just learn how to use a single library or framework, you’ll actually discover how to build these algorithms completely from scratch!Professional instructor Beau Carnes breaks deep learning wide open, drawing together his expertise in video instruction and Andrew Trask’s unique, intuitive approach from Grokking Deep Learning! As you move through this course, you’ll learn the fundamentals of deep learning from a unique standing!
Using Python, as well as Jupyter Notebooks, you’ll get stuck right in to the basics of neural prediction and learning, and teach your algorithms to visualize things like different weights. 01 Introduction02 What you need to get started03 What is Deep Learning and Machine Learning04 Supervised vs. Unsupervised learning05 Parametric vs.
Artificial Intelligence is one of the most exciting technologies of the century, and Deep Learning is in many ways the “brain” behind some of the world’s smartest Artificial Intelligence systems out there. Loosely based on neuron behavior inside of human brains, these systems are rapidly catching up with the intelligence of their human creators, defeating the world champio Artificial Intelligence is one of the most exciting technologies of the century, and Deep Learning is in many ways the “brain” behind some of the world’s smartest Artificial Intelligence systems out there. Loosely based on neuron behavior inside of human brains, these systems are rapidly catching up with the intelligence of their human creators, defeating the world champion Go player, achieving superhuman performance on video games, driving cars, translating languages, and sometimes even helping law enforcement fight crime. Deep Learning is a revolution that is changing every industry across the globe.Grokking Deep Learning is the perfect place to begin your deep learning journey. Rather than just learn the “black box” API of some library or framework, you will actually understand how to build these algorithms completely from scratch. You will understand how Deep Learning is able to learn at levels greater than humans.
In his engaging style, seasoned deep learning expert Andrew Trask shows you the science under the hood, so you grok for yourself every detail of training neural networks. Deep learning, a branch of artificial intelligence, teaches computers to learn by using neural networks, technology inspired by the human brain. Grokking deep learning Download grokking deep learning or read online here in PDF or EPUB. Please click button to get grokking deep learning book now. All books are in clear copy here, and all files are secure so don't worry about it.
You will be able to understand the “brain” behind state-of-the-art Artificial Intelligence. Furthermore, unlike other courses that assume advanced knowledge of Calculus and leverage complex mathematical notation, if you’re a Python hacker who passed high-school algebra, you’re ready to go. And at the end, you’ll even build an A.I. That will learn to defeat you in a classic Atari game. This was a great read. At first I had qualms about its usefullness, but the more I read the more I liked this. Even though it does not include many mathematics, it is great at tying the maths to a more abstract, high-level understanding.The way the concepts are described is delightful and intuitive, and the Python code helps in a lot of cases.
I did have to skip some parts, as I didn't find much use, but overall it was a great refresher for previous knowledge. Plus, it helped me understand some This was a great read. At first I had qualms about its usefullness, but the more I read the more I liked this.
Even though it does not include many mathematics, it is great at tying the maths to a more abstract, high-level understanding.The way the concepts are described is delightful and intuitive, and the Python code helps in a lot of cases. I did have to skip some parts, as I didn't find much use, but overall it was a great refresher for previous knowledge. Plus, it helped me understand some concepts more deeply.All in all, if you are prepared to skip ahead at times and want to gain a more intuitive understanding of Deep Learning, I highly recommend this book.
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