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Machine Learning Concepts with Python and the Jupyter Notebook Environment

Language EnglishEnglish
Book Paperback
Book Machine Learning Concepts with Python and the Jupyter Notebook Environment Nikita Silaparasetty
Libristo code: 28319709
Publishers APress, September 2020
Create, execute, modify, and share machine learning applications with Python and TensorFlow 2.0 in t... Full description
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Create, execute, modify, and share machine learning applications with Python and TensorFlow 2.0 in the Jupyter Notebook environment. This book breaks down any barriers to programming machine learning applications through the use of Jupyter Notebook instead of a text editor or a regular IDE. You'll start by learning how to use Jupyter Notebooks to improve the way you program with Python. After getting a good grounding in working with Python in Jupyter Notebooks, you'll dive into what TensorFlow is, how it helps machine learning enthusiasts, and how to tackle the challenges it presents. Along the way, sample programs created using Jupyter Notebooks allow you to apply concepts from earlier in the book. Those who are new to machine learning can dive in with these easy programs and develop basic skills. A glossary at the end of the book provides common machine learning and Python keywords and definitions to make learning even easier. What You Will Learn Program in Python and TensorFlow Tackle basic machine learning obstacles Develop in the Jupyter Notebooks environment Who This Book Is For Ideal for new Data Scientists and Machine Learning/Deep Learning enthusiasts who are interested in programming with Python using Tensorflow 2.0 in the Jupyter Notebook Application. Some basic knowledge of Machine Learning concepts and Python Programming (using Python version 3) is helpful.

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About the book

Full name Machine Learning Concepts with Python and the Jupyter Notebook Environment
Language English
Binding Book - Paperback
Date of issue 2020
Number of pages 290
EAN 9781484259665
Libristo code 28319709
Publishers APress
Weight 416
Dimensions 233 x 154 x 30
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