TensorFlow Absolute For Beginners Tutorial [2024, EPUB, ENG] torrent

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TensorFlow Absolute For Beginners Tutorial

Год издания: 2024

Издательство: Kavi & Shila
ASIN: B0D6FCJHMS
Язык: Английский

Формат: EPUB
Качество: Издательский макет или текст (eBook)
Интерактивное оглавление: Да
Количество страниц: 111

Описание: Have you ever wondered how computers can learn and make intelligent decisions? This book is your entry point to the world of Machine Learning with TensorFlow, Google's powerful open-source library.
Even if you have no prior experience with Machine Learning or coding, this book will gently guide you through the fundamentals. You'll build a solid understanding of key concepts like:
- What machine learning is and its exciting applications
- Grasping the core idea of tensors, the building blocks of TensorFlow
- Unveiling the computational graph, the heart of TensorFlow programs
- Hands-on exercises to practice building basic machine learning models
Through practical examples and clear explanations, you'll learn how to:
- Install and set up TensorFlow
- Work with data in TensorFlow
- Craft simple machine learning models like linear regression
- Train your models and understand the training process
[spoiler="Примеры страниц (скриншоты)"]

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[spoiler="Оглавление"]
Chapter - 1 : Introduction
Chapter - 2 : Installation
Chapter - 3 : Understanding Artificial Intelligence
Chapter - 4 : Mathematical Foundations
Chapter - 5 : Machine Learning and Deep Learning
Chapter - 6 : Basics
Chapter - 7 : Convolutional Neural Networks
Chapter - 8 : Recurrent Neural
Chapter - 9 : TensorBoard Visualization
Chapter - 10 : Word Embedding
Chapter - 11 : Single Layer Perceptron
Chapter - 12 : Linear Regression
Chapter - 13 : TFLearn And Its Installation
Chapter - 14 : CNN And RNN Difference
Chapter - 15 : Keras
Chapter - 16 : Distributed Computing
Chapter - 17 : Exporting
Chapter - 18 : Multi-Layer Perceptron Learning
Chapter - 19 : Hidden Layers of Perceptron
Chapter - 20 : Optimizers
Chapter - 21 : XOR Implementation
Chapter - 22 : Gradient Descent Optimization
Chapter - 23 : Forming Graphs
Chapter - 24 : Image Recognition using TensorFlow
Chapter - 25 : Recommendations for Neural Network Training
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