Python for Programmers: With Introductory Al Case Studies
Publication details: Noida: Pearson, 2020Description: 599ISBN:- 9789353947989
- 005.133 (PYT)
Item type | Current library | Collection | Call number | Status | Date due | Barcode | Item holds | |
---|---|---|---|---|---|---|---|---|
Reference Book | Alliance College of Engineering and Design | CSE & IT | 005.133 (PYT) (Browse shelf(Opens below)) | Not for loan | E13777 | |||
Book | Alliance College of Engineering and Design | CSE & IT | 005.133 (PYT) (Browse shelf(Opens below)) | Checked out | 23/12/2024 | E13779 | ||
Book | Alliance College of Engineering and Design | CSE & IT | 005.133 (PYT) (Browse shelf(Opens below)) | Available | E13778 | |||
Book | Alliance College of Engineering and Design | CSE & IT | 005.133 (PYT) (Browse shelf(Opens below)) | Available | E13781 | |||
Book | Alliance College of Engineering and Design | CSE & IT | 005.133 (PYT) (Browse shelf(Opens below)) | Available | E13780 |
Written for programmers with a background in another high-level language, this book uses hands-on instruction to teach today's most compelling, leading-edge computing technologies and programming in Python—one of the world's most popular and fastest-growing languages. Please read the Table of Contents diagram inside the front cover and the Preface for more details. Table of Content "Chapter 1: Introduction to Computers and Python Chapter 2: Introduction to Python Programming Chapter 3: Control Statements Chapter 4: Functions Chapter 5: Sequences: Lists and Tuples Chapter 6: Dictionaries and Sets Chapter 7: Array-Oriented Programming with NumPy Chapter 8: Strings: A Deeper Look Chapter 9: Files and Exceptions Chapter 10: Object-Oriented Programming Chapter 11: Natural Language Processing (NLP) Chapter 12: Data Mining Twitter Chapter 13: IBM Watson and Cognitive Computing Chapter 14: Machine Learning: Classification, Regression and Clustering Chapter 15: Deep Learning Chapter 16: Big Data: Hadoop, Spark, NoSQL and IoT " Salient Features "· 500+ hands-on, real-world, live-code examples from snippets to case studies · IPython + code in Jupyter® Notebooks · Library-focused: Uses Python Standard Library and data science libraries to accomplish significant tasks with minimal code · Rich Python coverage: Control statements, functions, strings, files, JSON serialization, CSV, exceptions · Procedural, functional-style and object-oriented programming"
There are no comments on this title.