Lisa Farina has narrated 4 audiobooks on Listento.it by 6 authors, with an average listener rating of 5★ across 4 ratings. The most-rated is Real-World Machine Learning.
Classic Computer Science Problems in Python
Summary
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 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) and Classic Computer Science Problems in Swift (Manning, 2018). Table of contents Small problems Search problems Constraint-satisfaction problems Graph problems Genetic algorithms K-means clustering Fairly simple neural networks Adversarial search Miscellaneous problems PLEASE NOTE: When you purchase this title, the accompanying PDF will be available in your Audible Library along with the audio.
©2019 Manning Publications (P)2019 Manning Publications
Real-World Machine Learning
Summary
Real-World Machine Learning will teach you the concepts and techniques you need to be a successful machine learning practitioner without overdosing you on abstract theory and complex mathematics. By working through immediately relevant examples in Python, you'll build skills in data acquisition and modeling, classification, and regression. You'll also explore the most important tasks like model validation, optimization, scalability, and real-time streaming. When you're done, you'll be ready to successfully build, deploy, and maintain your own powerful ML systems. Machine learning systems help you find valuable insights and patterns in data, which you'd never recognize with traditional methods. In the real world, ML techniques give you a way to identify trends, forecast behavior, and make fact-based recommendations. It's a hot and growing field, and up-to-speed ML developers are in demand. What's inside: Predicting future behavior Performance evaluation and optimization Analyzing sentiment and making recommendations No prior machine learning experience assumed, but you should know Python. Henrik Brink, Joseph Richards, and Mark Fetherolf are experienced data scientists engaged in the daily practice of machine learning. Table of Contents: The Machine-Learning Workflow 1. What is machine learning? 2. Real-world data 3. Modeling and prediction 4. Model evaluation and optimization 5. Basic feature engineering PRACTICAL APPLICATION 6. Example: NYC taxi data 7. Advanced feature engineering 8. Advanced NLP example: movie review sentiment 9. Scaling machine-learning workflows 10. Example: digital display advertising PLEASE NOTE: When you purchase this title, the accompanying PDF will be available in your Audible Library along with the audio.
©2016 Manning Publications (P)2016 Manning Publications
Practices of the Python Pro
Summary
Professional developers know the many benefits of writing application code that’s clean, well-organized, and easy to maintain. By learning and following established patterns and best practices, you can take your code and your career to a new level. With Practices of the Python Pro, you’ll learn to design professional-level, clean, easily maintainable software at scale using the incredibly popular programming language, Python. You’ll find easy-to-grok examples that use pseudocode and Python to introduce software development best practices, along with dozens of instantly useful techniques that will help you code like a pro. About the technology Professional-quality code does more than just run without bugs. It’s clean, readable, and easy to maintain. To step up from a capable Python coder to a professional developer, you need to learn industry standards for coding style, application design, and development process. That’s where this book is indispensable. About the book Practices of the Python Pro teaches you to design and write professional-quality software that’s understandable, maintainable, and extensible. Dane Hillard is a Python pro who has helped many dozens of developers make this step, and he knows what it takes. With helpful examples and exercises, he teaches you when, why, and how to modularize your code, how to improve quality by reducing complexity, and much more. Embrace these core principles, and your code will become easier for you and others to read, maintain, and reuse. What's inside Organizing large Python projects Achieving the right levels of abstraction Writing clean, reusable code Inheritance and composition Considerations for testing and performance About the audience For learners familiar with the basics of Python or another OO language. About the author Dane Hillard has spent the majority of his development career using Python to build web applications.
©2019 Manning Publications (P)2021 Manning Publications
C++ Concurrency in Action, Second Edition
Summary
This best seller has been updated and revised to cover all the latest changes to C++ 14 and 17! C++ Concurrency in Action, Second Edition teaches you everything you need to write robust and elegant multithreaded applications in C++17. About the Technology You choose C++ when your applications need to run fast. Well-designed concurrency makes them go even faster. C++ 17 delivers strong support for the multithreaded, multiprocessor programming required for fast graphic processing, machine learning, and other performance-sensitive tasks. This exceptional audiobook unpacks the features, patterns, and best practices of production-grade C++ concurrency. About the Book C++ Concurrency in Action, Second Edition is the definitive guide to writing elegant multithreaded applications in C++. Updated for C++ 17, it carefully addresses every aspect of concurrent development, from starting new threads to designing fully functional multithreaded algorithms and data structures. Concurrency master Anthony Williams presents examples and practical tasks in every section, including insights that will delight even the most experienced developer. What's Inside Full coverage of new C++ 17 features Starting and managing threads Synchronizing concurrent operations Designing concurrent code Debugging multithreaded applications About the Reader/Listener Written for intermediate C and C++ developers. No prior experience with concurrency required. About the Author Anthony Williams has been an active member of the BSI C++ Panel since 2001 and is the developer of the just::thread Pro extensions to the C++ 11 thread library. PLEASE NOTE: When you purchase this title, the accompanying PDF will be available in your Audible Library along with the audio.
©2019 Manning Publications (P)2019 Manning Publications