DEEP LEARNING: FROM BIG DATA TO ARTIFICIAL INTELLIGENCE WITH R
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DESCRIPTION
DEEP LEARNING
A concise and practical exploration of key topics and applications in data science
In Deep Learning: From Big Data to Artificial Intelligence with R, expert researcher Dr. Stéphane Tufféry delivers an insightful discussion of the applications of deep learning and big data that focuses on practical instructions on various software tools and deep learning methods relying on three major libraries: MXNet, PyTorch, and Keras-TensorFlow. In the book, numerous, up-to-date examples are combined with key topics relevant to modern data scientists, including processing optimization, neural network applications, natural language processing, and image recognition.
This is a thoroughly revised and updated edition of a book originally released in French, with new examples and methods included throughout. Classroom-tested and intuitively organized, Deep Learning: From Big Data to Artificial Intelligence with R offers complimentary access to a companion website that provides R and Python source code for the examples offered in the book. Readers will also find:
A thorough introduction to practical deep learning techniques with explanations and examples for various programming libraries
Comprehensive explorations of a variety of applications for deep learning, including image recognition and natural language processing
Discussions of the theory of deep learning, neural networks, and artificial intelligence linked to concrete techniques and strategies commonly used to solve real-world problems
Perfect for graduate students studying data science, big data, deep learning, and artificial intelligence, Deep Learning: From Big Data to Artificial Intelligence with R will also earn a place in the libraries of data science researchers and practicing data scientists.
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Intro to Python for Computer Science and Data Science: Learning to Program with AI, Big Data and the Cloud (1版)
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目錄大綱
Table of Contents:
1. Introduction to Computers and Python
2. Introduction to Python Programming
3. Control Statements and Program Development
4. Functions
5. Sequences: Lists and Tuples
6. Dictionaries and Sets
7. Array-Oriented Programming with NumPy
8. Strings: A Deeper Look
9. Files and Exceptions
10. Object-Oriented Programming
11. Computer Science Thinking: Recursion, Searching, Sorting and Big O
12. Natural Language Processing (NLP)
13. Data Mining Twitter
14. IBM Watson and Cognitive Computing
15. Machine Learning: Classification, Regression and Clustering
16. Deep Learning
17. Big Data: Hadoop, Spark, NoSQL and IoT
Index
目錄大綱(中文翻譯)
目錄:
1. 電腦和Python簡介
2. Python程式設計簡介
3. 控制語句和程式開發
4. 函式
5. 序列:列表和元組
6. 字典和集合
7. 使用NumPy進行陣列導向程式設計
8. 字串:更深入的觀察
9. 檔案和例外處理
10. 物件導向程式設計
11. 電腦科學思維:遞迴、搜尋、排序和Big O
12. 自然語言處理(NLP)
13. 探勘Twitter資料
14. IBM Watson和認知運算
15. 機器學習:分類、回歸和分群
16. 深度學習
17. 大數據:Hadoop、Spark、NoSQL和物聯網
索引
原價:
1480
售價:
1406
現省:
74元
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