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Titlebook: Machine Learning Concepts with Python and the Jupyter Notebook Environment; Using Tensorflow 2.0 Nikita Silaparasetty Book 2020 Nikita Sila

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發(fā)表于 2025-3-21 16:21:53 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書(shū)目名稱Machine Learning Concepts with Python and the Jupyter Notebook Environment
副標(biāo)題Using Tensorflow 2.0
編輯Nikita Silaparasetty
視頻videohttp://file.papertrans.cn/621/620392/620392.mp4
概述Gain comfort in the Jupyter Notebooks environment, which makes programming in Python even easier.Build a basic understanding of more complex Machine Learning concepts and how TensorFlow simplifies the
圖書(shū)封面Titlebook: Machine Learning Concepts with Python and the Jupyter Notebook Environment; Using Tensorflow 2.0 Nikita Silaparasetty Book 2020 Nikita Sila
描述. .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.Programin Python and TensorFlow.Tacklebasic machine learning obstacles.Developin the Jupyter Notebooks environment.Who This Book Is For.Ideal for Machine Learning and Deep Learning enthusiasts who are interested in programming with Py
出版日期Book 2020
關(guān)鍵詞TensorFlow; Deep Learning; Machine Learning; Jupyter Notebook; Python
版次1
doihttps://doi.org/10.1007/978-1-4842-5967-2
isbn_softcover978-1-4842-5966-5
isbn_ebook978-1-4842-5967-2
copyrightNikita Silaparasetty 2020
The information of publication is updating

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發(fā)表于 2025-3-22 03:47:24 | 只看該作者
Introduction to Jupyter Notebook, however, is not the most recommended tool to use when it comes to massive machine learning programming. This is why we have developed applications like Jupyter Notebook, which aid in such programming requirements.
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發(fā)表于 2025-3-22 07:17:18 | 只看該作者
Introducing Tensorflow 2.0till in its alpha version. Despite its being an unofficial release, it had already gathered quite a bit of attention from programmers, who soon realized that it was definitely a significant improvement from what it used to be.
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發(fā)表于 2025-3-22 16:17:11 | 只看該作者
erblick bei Br?uer/Winkler 2012). Die zu beobachtende Konsolidierung legt es nun aber zugleich nahe, nach der Justierung dieser Forschungsrichtung genauer zu fragen: Welche Zielsetzungen werden bzw. sollen verfolgt werden? Lassen sich Aussagen über geeignete Forschungsdesigns treffen? Welche Verknüp
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發(fā)表于 2025-3-22 22:50:58 | 只看該作者
Nikita Silaparasettyklung eines institutionalisierten, ?ffentlichen, im Prinzip allen Kindern und Jugendlichen zug?nglichen Bildungswesens er?ffnet der heranwachsenden Generation bis dato einmalige Bildungschancen. Dass diese auch vermehrt genutzt werden, zeigt die Entwicklung der Schülerzahlen in den letzten Jahren; D
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發(fā)表于 2025-3-23 04:46:16 | 只看該作者
die historische und gesellschaftliche Entwicklung eines institutionalisierten, ?ffentlichen, im Prinzip allen Kindern und Jugendlichen zug?nglichen Bildungswesens der heranwachsenden Generation bis dato einmalige Bildungschancen er?ffnet. Dass diese auch vermehrt genutzt werden, zeigt sich mit Blick
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發(fā)表于 2025-3-23 06:34:58 | 只看該作者
Nikita Silaparasettynzepte. Im ersten Teil werden — ausgehend vom Bedeutungshof des Begriffs ?Intelligenz“ und seiner wissenschaftlichen Verwendung — exemplarisch drei Intelligenzmodelle vorgestellt: Spearmans Generalfaktormodell, Thurstones Modell der Prim?rf?higkeiten und ein hierarchisches Modell als Synthese dieser
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