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Książki \ Programowanie \ Python

Intro to Python for Computer Science and Data Science: Learning to Program with AI, Big Data and The Cloud Język: 2

978-0-13-540467-6

Cena Brutto: 363.93

Cena netto: 346.60

Ilość:
Wersja: Drukowana
Autor Paul J. Deitel, Harvey Deitel
Liczba_stron 880
Wydawnictwo Pearson
Data_Wydania 2019-06-05
Intro to Python for Computer Science and Data Science: Learning to Program with AI, Big Data and The Cloud

The Deitels Introduction to Python for Computer Science and Data Science: Learning to Program with AI, Big Data and the Cloud offers a unique approach to teaching introductory Python programming, appropriate for both computer-science and data-science audiences. Providing the most current coverage of topics and applications, the book is paired with extensive traditional supplements as well as Jupyter Notebooks supplements. Real-world datasets and artificial-intelligence technologies allow students to work on projects making a difference in business, industry, government and academia. Hundreds of examples, exercises, projects (EEPs), and implementation case studies give students an engaging, challenging and entertaining introduction to Python programming and hands-on data science.


The books modular architecture enables instructors to conveniently adapt the text to a wide range of computer-science and data-science courses offered to audiences drawn from many majors. Computer-science instructors can integrate as much or as little data-science and artificial-intelligence topics as theyd like, and data-science instructors can integrate as much or as little Python as theyd like. The book aligns with the latest ACM/IEEE CS-and-related computing curriculum initiatives and with the Data Science Undergraduate Curriculum Proposal sponsored by the National Science Foundation.

PART 1

CS: Python Fundamentals Quickstart

CS 1. Introduction to Computers and Python

DS Intro: AI–at the Intersection of CS and DS

CS 2. Introduction to Python Programming

DS Intro: Basic Descriptive Stats

CS 3. Control Statements and Program Development

DS Intro: Measures of Central Tendency—Mean, Median, Mode

CS 4. Functions

DS Intro: Basic Statistics— Measures of Dispersion

CS 5. Lists and Tuples

DS Intro: Simulation and Static Visualization

PART 2

CS: Python Data Structures, Strings and Files

CS 6. Dictionaries and Sets

DS Intro: Simulation and Dynamic Visualization

CS 7. Array-Oriented Programming with NumPy, High-Performance NumPy Arrays

DS Intro: Pandas Series and DataFrames

CS 8. Strings: A Deeper Look Includes Regular Expressions

DS Intro: Pandas, Regular Expressions and Data Wrangling

CS 9. Files and Exceptions

DS Intro: Loading Datasets from CSV Files into Pandas DataFrames

PART 3

CS: Python High-End Topics

CS 10. Object-Oriented Programming

DS Intro: Time Series and Simple Linear Regression

CS 11. Computer Science Thinking: Recursion, Searching, Sorting and Big O

CS and DS Other Topics Blog


PART 4

AI, Big Data and Cloud Case Studies

DS 12. Natural Language Processing (NLP), Web Scraping in the Exercises

DS 13. Data Mining Twitter®: Sentiment Analysis, JSON and Web Services

DS 14. IBM Watson® and Cognitive Computing

DS 15. Machine Learning: Classification, Regression and Clustering

DS 16. Deep Learning Convolutional and Recurrent Neural Networks; Reinforcement Learning in the Exercises

DS 17. Big Data: Hadoop®, Spark™, NoSQL and IoT

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