March 2018
Intermediate to advanced
320 pages
7h 53m
English
book
TensorFlow Deep Learning Projects
by Alexey Grigorev, Srinivas Kulkarni, Rajalingappaa Shanmugamani
Overview
Embark on an engaging journey into TensorFlow deep learning by exploring 10 practical projects that focus on real-world challenges. This book will guide you through mastering TensorFlow tools and models for innovative projects such as creating chatbots, predicting stock prices, and developing AI that plays video games. You'll deepen your skills and build functional systems to solve complex problems.
What this Book will help me do
- Understand how to set up TensorFlow for efficient deep learning workflows.
- Build convolutional neural networks for advancements in image recognition projects.
- Develop chatbots powered by deep neural networks to provide natural language responses.
- Implement advanced LSTM models for accurate time series forecasting and text processing.
- Experiment with GANs to create synthetic data and novel image creation capabilities.
Author(s)
Alexey Grigorev and None Shanmugamani are seasoned machine learning practitioners and educators. Alexey focuses on data science and deep learning solutions for complex problems, while None specializes in TensorFlow-powered AI systems. Together, they bring practical experience and an accessible teaching style to this book.
Who is it for?
This book is ideal for data scientists, machine learning developers, and deep learning practitioners with a basic grasp of TensorFlow who aspire to enhance their expertise. It's designed for those interested in hands-on projects that connect the theory of deep learning to practical applications. Readers should have foundational knowledge of machine learning principles to fully benefit from the book.
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