Artificial Intelligence and Deep Learning with Python Every Line of Code Explained (Chinese Version): For Readers New to AI and New to Python: 每行代码详解 面向 AI 和 Python 新手读者 - Tapa blanda

Sinopsis

This is the Chinese language version of the 5 star reviewed English text. Frustrated by deep learning books and videos that don’t explain each and every line of code? Artificial Intelligence and Deep Learning with Python is far ahead of the rest when it comes to books explaining deep learning, AI and python to beginners of deep learning, AI and python. Frustrated by deep learning books and videos that don’t explain each and every line of code? Artificial Intelligence and Deep Learning with Python is far ahead of the rest when it comes to books explaining deep learning, AI and python to beginners of deep learning, AI and python. This is the Chinese language version of the 5 star reviewed English text. The author of this text 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 each part of a line of code is not explained to you, 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/deep learning 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 artificial intelligence with Thompson sampling
• Using deep learning to predict crime statistics
• Using neural networks for binary classification
• 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

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