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Machine learning concepts with Python and the Jupyter Notebook environment : using Tensorflow 2.0 /
Create, execute, modify, and share machine learning applications with Python in the Jupyter Notebook environment. This book breaks down any barriers to programming machine learning applications through the use of Jupyter Notebooks instead of a text editor or a regular IDE. Youll start by learning fu...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
[Berkeley, CA] :
Apress,
[2020]
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| Temas: | |
| Acceso en línea: | Texto completo (Requiere registro previo con correo institucional) |
MARC
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| 100 | 1 | |a Silaparasetty, Nikita, |e author. | |
| 245 | 1 | 0 | |a Machine learning concepts with Python and the Jupyter Notebook environment : |b using Tensorflow 2.0 / |c Nikita Silaparasetty. |
| 264 | 1 | |a [Berkeley, CA] : |b Apress, |c [2020] | |
| 300 | |a 1 online resource (XXVII, 290 pages) : |b illustrations | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
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| 500 | |a Includes index. | ||
| 505 | 0 | |a Chapter 1: An Overview of Artificial Intelligence -- Chapter 2: An Overview of Machine Learning -- Chapter 3: Introduction to Deep Learning -- Chapter 4: Machine Learning Versus Deep Learning -- Chapter 5: Machine Learning with Python -- Chapter 6: Introduction to Jupyter Notebooks -- Chapter 7: Python Programming on the Jupyter Notebook -- Chapter 8: The Tensorflow Machine Learning Library -- Chapter 9: Programming with Tensorflow 1.0 -- Chapter 10: Introducing TensorFlow 2.0 -- Chapter 11: Machine Learning Programming with TensorFlow 2.0. | |
| 520 | |a Create, execute, modify, and share machine learning applications with Python in the Jupyter Notebook environment. This book breaks down any barriers to programming machine learning applications through the use of Jupyter Notebooks instead of a text editor or a regular IDE. Youll start by learning fundamental concepts in Python necessary for working with machine learning application development. Then use Jupyter Notebooks to improve the way you program with Python. After grounding your skills in working with Python in Jupyter Notebooks, youll 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 start 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. You will: Program machine learning models in Python Tackle basic machine learning obstacles Develop in the Jupyter Notebooks environment. | ||
| 506 | 1 | |a Legal Deposit; |c Only available on premises controlled by the deposit library and to one user at any one time; |e The Legal Deposit Libraries (Non-Print Works) Regulations (UK). |5 WlAbNL | |
| 588 | 0 | |a Online resource; title from digital title page (viewed on November 09, 2020). | |
| 590 | |a O'Reilly |b O'Reilly Online Learning: Academic/Public Library Edition | ||
| 630 | 0 | 0 | |a TensorFlow. |
| 650 | 0 | |a Machine learning. | |
| 650 | 0 | |a Python (Computer program language) | |
| 650 | 0 | |a Information visualization. | |
| 650 | 6 | |a Apprentissage automatique. | |
| 650 | 6 | |a Python (Langage de programmation) | |
| 650 | 6 | |a Visualisation de l'information. | |
| 650 | 7 | |a Artificial intelligence. |2 bicssc | |
| 650 | 7 | |a Computers |x Intelligence (AI) & Semantics. |2 bisacsh | |
| 650 | 7 | |a Information visualization |2 fast | |
| 650 | 7 | |a Machine learning |2 fast | |
| 650 | 7 | |a Python (Computer program language) |2 fast | |
| 776 | 0 | 8 | |i Print version: |a Silaparasetty, Nikita. |t Machine Learning Concepts with Python and the Jupyter Notebook Environment : Using Tensorflow 2. 0. |d Berkeley, CA : Apress L.P., ©2020 |z 9781484259665 |
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