”Highly recommended to everyone interested in deepening their understanding of Python and practical computer science.” | Key Features > Master formal techniques taught in college computer science classes > Connect computer science theory to real-world applications, data, and performance > Prepare for programmer interviews > Recognize the core ideas behind most “new” challenges > Covers Python 3.7 Note: Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.
About The Book
Programming problems that seem new or unique are usually rooted in well-known engineering principles. Classic Computer Science Problems in Python guides you through time-tested scenarios, exercises, and algorithms that will prepare you for the “new” problems you’ll face when you start your next project.
In this amazing book, you'll tackle dozens of coding challenges, ranging from simple tasks like binary search algorithms to clustering data using k-means. As you work through examples for web development, machine learning, and more, you'll remember important things you've forgotten and discover classic solutions that will save you hours of time.
What You Will Learn
• Search algorithms
• Common techniques for graphs
• Neural networks
• Genetic algorithms
• Adversarial search
• Uses type hints throughout
This Book Is Written For
For intermediate Python programmers.
About The Author
David Kopec is an assistant professor of Computer Science and Innovation at Champlain College in Burlington, Vermont. He is the author of Dart for Absolute Beginners (Apress, 2014), Classic Computer Science Problems in Swift (Manning, 2018), and Classic Computer Science Problems in Java (Manning, 2020)
Table of Contents
1. Small problems
2. Search problems
3. Constraint-satisfaction problems
4. Graph problems
5. Genetic algorithms
6. K-means clustering
7. Fairly simple neural networks
8. Adversarial search
9. Miscellaneous problems
"synopsis" may belong to another edition of this title.
"About this title" may belong to another edition of this title.
Seller: HPB-Red, Dallas, TX, U.S.A.
Paperback. Condition: Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority! Seller Inventory # S_436805388
Seller: ThriftBooks-Dallas, Dallas, TX, U.S.A.
Paperback. Condition: Very Good. No Jacket. May have limited writing in cover pages. Pages are unmarked. ~ ThriftBooks: Read More, Spend Less. Seller Inventory # G1617295981I4N00
Seller: HPB-Diamond, Dallas, TX, U.S.A.
Paperback. Condition: Very Good. Connecting readers with great books since 1972! Used books may not include companion materials, and may have some shelf wear or limited writing. We ship orders daily and Customer Service is our top priority! Seller Inventory # S_453819128
Seller: Better World Books: West, Reno, NV, U.S.A.
Condition: Good. Former library book; may include library markings. Used book that is in clean, average condition without any missing pages. Seller Inventory # 53523070-75
Seller: Broad Street Books, Branchville, NJ, U.S.A.
paperback. Condition: As New. Book is in excellent condition, text is unmarked and pages are tight. Seller Inventory # f15256
Seller: WorldofBooks, Goring-By-Sea, WS, United Kingdom
Paperback. Condition: Very Good. The book has been read, but is in excellent condition. Pages are intact and not marred by notes or highlighting. The spine remains undamaged. Seller Inventory # GOR011596902
Quantity: 1 available
Seller: Grand Eagle Retail, Bensenville, IL, U.S.A.
Paperback. Condition: new. Paperback. Classic Computer Science Problems in Python presents dozens of coding challenges, ranging from simple tasks like finding items in a list with a binary sort algorithm to clustering data using k-means. Classic Computer Science Problems in Python deepens your Python language skills by challenging you with time-tested scenarios, exercises, and algorithms. As you work through examples in search, clustering, graphs, and more, you'll remember important things you've forgotten and discover classic solutions to your "new" problems Key Features Breadth-first and depth-first search algorithms Constraints satisfaction problems Common techniques for graphs Adversarial Search Neural networks and genetic algorithms Written for data engineers and scientists with experience using Python. For readers comfortable with the basics of Python About the technology Python is used everywhere for web applications, data munging, and powerful machine learning applications. Even problems that seem new or unique stand on the shoulders of classic algorithms, coding techniques, and engineering principles. Master these core skills, and youll be ready to use Python for AI, data-centric programming, deep learning, and the other challenges youll face as you grow your skill as a programmer. David Kopec teaches at Champlain College in Burlington, VT and is the author of Mannings Classic Computer Science Problemsin Swift. "For intermediate Python programmers"--Back cover. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9781617295980
Seller: upickbook, Daly City, CA, U.S.A.
paperback. Condition: New. Seller Inventory # mon0000250835
Seller: Books Puddle, New York, NY, U.S.A.
Condition: New. pp. 224. Seller Inventory # 26379725410
Seller: PBShop.store UK, Fairford, GLOS, United Kingdom
PAP. Condition: New. New Book. Shipped from UK. Established seller since 2000. Seller Inventory # PB-9781617295980
Quantity: 15 available