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[New] Concise and Practical AI/ML
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Preface
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This book is about AI and ML with the details from work of the author with more focus on practical aspects. All samples are mainly in Python, and TensorFlow.
This book is promoting the concept of, where Genetics is the known processes (algorithms) and the known data, machine learning is what learnt during lifetime of AI:
AI = Genetics + ML
The book aims to provide a concise and practical approach to the knowledge boundary of AI and ML, mainly from the experience of the author at work.
Everything in this book is a try to express the meaning of that thing the core and simple way, however, with a guiding person to read is better. AI is involving multiple algorithms, but the aim of this book will be focused mostly only machine learning and with a try to cover all topics in machine learning.
Some related knowledge related to machine learning are also mentioned, for example, biology and mathematics.
This book will almost always use TensorFlow to make examples, although PyTorch can be academic but TensorFlow is more popular and somehow with better design with activation function inside layer.
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