Artificial Intelligence and Deep Learning with Python: Every Line of Code Explained For Readers New to AI and New to Python
Format:
Paperback
En stock
0.92 kg
Sí
Nuevo
Amazon
USA
- Frustrated by deep learning books and videos that don’t explain each and every line of code? Artificial Intelligence and Deep Learning with Python (2nd Edition) is far ahead of the competition when it comes to books explaining deep learning, AI and python to beginners of deep learning, AI and python. The author believes that a computer language is like any other language. If you don’t know what each part of a sentence means then you will never completely understand how to write new sentences. Similarly, if you don’t know what each part of the code means, how can you write new original code? Why do so many books claiming to be for “beginners” not explain each and every line of code? Is it due to laziness, too much effort, or actually not wanting to teach readers about the subject? What can be more frustrating than having a few lines of code explained and then the next line is not explained or having only part of a line of code explained? In this text you will find ample explanations for each line of code for each project presented. In addition you will see thorough explanations of deep learning and AI concepts. The text is intended for those new to python as well as experienced programmers in python. For readers who are familiar with python, this book will guide them through applying deep learning’s “language of choice” to fascinating and varied AI projects. The author even gives his email to attempt to assist the readers with the projects. Projects and topics include: Applying deep learning to audio/music and voice recognition Working with neural networks and image files Creating a stock price prediction algorithm Using deep learning to make predictions Building a convolutional neural network to classify your own image files Train your computer to “read” and “understand” the English language Using SQL in neural networks Creating original images with generative AI About the 2nd Edition: The 2nd edition contains additions and improvements over the 1st edition. There is a new section on generative AI and autoencoders: a growing and controversial field since generative AI is used to create artificial photos, videos, audio, music and more. Existing texts, videos, and websites are frequently not written for the beginner and tend to give confusing explanations of the code if the code is explained at all. The section on generative AI and autoencoders explains every line of code and provides diagrams which facilitate understanding of the concepts which would otherwise seem complex to a beginner. The second edition also contains improved explanations for convolutional neural networks and long term short term memory neural networks which the 1st edition was lacking. The new CNN and LSTM sections contain new diagrams which aid in the understanding of these complex models to help novices to AI. There is a brand new section on bidirectional LSTMs. These complex models improve on traditional LSTMs in predicting the future. And of course, as usual, every line of code is explained. Also included is a new section entitled Different Ways to Create a Neural Network, improving on the 2nd chapter of the 1st edition. About the Author: Steven D’Ascoli is an adjunct professor at St. John’s University. He has also taught management information systems at the City University of New York. He is a CPA and obtained his CCNA (Cisco Certified Network Associate) certification. He is also a financial analyst for one of the largest organizations in the U.S. He studied computer science at Columbia University from which he holds a bachelor's degree. He also studied computer programming at NYU, from which he holds a master's degree. He also created the first community of practice for artificial intelligence in one of the largest U.S. government agencies.
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