Classic Computer Science Problems in Python
- 5h 5m 56s
- David Kopec
- Manning Publications
- 2019
Classic Computer Science Problems in Python sharpens your CS problem-solving skills with time-tested scenarios, exercises, and algorithms, using Python. You'll tackle dozens of coding challenges, ranging from simple tasks like binary search algorithms to clustering data using k-means. You'll especially enjoy the feeling of satisfaction as you crack problems that connect computer science to the real-world concerns of apps, data, performance, and even nailing your next job interview!
Computer science problems that seem new or unique are often rooted in classic algorithms, coding techniques, and engineering principles. And classic approaches are still the best way to solve them! Understanding these techniques in Python expands your potential for success in web development, data munging, machine learning, and more.
What's inside
- Search algorithms
- Common techniques for graphs
- Neural networks
- Genetic algorithms
- Adversarial search
- Uses type hints throughout
- Covers Python 3.7
In this Audiobook
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Chapter 1 - Small Problems
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Chapter 2 - Search Problems
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Chapter 3 - Constraint-Satisfaction Problems
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Chapter 4 - Graph Problems
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Chapter 5 - Genetic Algorithms
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Chapter 6 - K-Means Clustering
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Chapter 7 - Fairly Simple Neural Networks
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Chapter 8 - Adversarial Search
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Chapter 9 - Miscellaneous Problems
