A Hands On Introduction To Essential Python Libraries And Frameworks With Code Samples
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A Hands-On Introduction to Essential Python Libraries and Frameworks (With Code Samples)
Essential Python libraries and frameworks that every aspiring data scientist, ML engineer, and Python developer should know. "Python is not just a language, it's a community where developers can learn, collaborate and create wonders." ~ Guido van Rossum (Creator of Python)
Applied Machine Learning for Data Science Practitioners
Author: Vidya Subramanian
language: en
Publisher: John Wiley & Sons
Release Date: 2025-04-01
A single-volume reference on data science techniques for evaluating and solving business problems using Applied Machine Learning (ML). Applied Machine Learning for Data Science Practitioners offers a practical, step-by-step guide to building end-to-end ML solutions for real-world business challenges, empowering data science practitioners to make informed decisions and select the right techniques for any use case. Unlike many data science books that focus on popular algorithms and coding, this book takes a holistic approach. It equips you with the knowledge to evaluate a range of techniques and algorithms. The book balances theoretical concepts with practical examples to illustrate key concepts, derive insights, and demonstrate applications. In addition to code snippets and reviewing output, the book provides guidance on interpreting results. This book is an essential resource if you are looking to elevate your understanding of ML and your technical capabilities, combining theoretical and practical coding examples. A basic understanding of using data to solve business problems, high school-level math and statistics, and basic Python coding skills are assumed. Written by a recognized data science expert, Applied Machine Learning for Data Science Practitioners covers essential topics, including: Data Science Fundamentals that provide you with an overview of core concepts, laying the foundation for understanding ML. Data Preparation covers the process of framing ML problems and preparing data and features for modeling. ML Problem Solving introduces you to a range of ML algorithms, including Regression, Classification, Ranking, Clustering, Patterns, Time Series, and Anomaly Detection. Model Optimization explores frameworks, decision trees, and ensemble methods to enhance performance and guide the selection of the most effective model. ML Ethics addresses ethical considerations, including fairness, accountability, transparency, and ethics. Model Deployment and Monitoring focuses on production deployment, performance monitoring, and adapting to model drift.
Hands-On Design Patterns with Python
Author: Aditya Pratap Bhuyan
language: en
Publisher: Aditya Pratap Bhuyan
Release Date: 2025-03-07
Hands-On Design Patterns with Python is an essential guide for software developers and engineers seeking to master design patterns and enhance their Python programming skills. Whether you're a beginner or an experienced Python developer, this book provides you with the tools and practical knowledge to implement and apply design patterns effectively in your projects. Design patterns are proven solutions to common software design challenges. This book dives into the 23 classic design patterns, categorizing them into Creational, Structural, and Behavioral patterns, offering real-world Python code examples and hands-on guidance. Each pattern is explained with clarity, demonstrating its real-world application and helping you write more modular, scalable, and maintainable code. Key Features: Comprehensive Coverage of Design Patterns: From fundamental patterns like Singleton and Factory to advanced ones like Command and State, this book covers a wide range of design patterns with easy-to-follow Python implementations. Practical Code Examples: Every pattern is accompanied by detailed Python code, showing you how to implement and adapt the pattern to solve common software design problems. Real-World Use Cases: Learn how to apply design patterns to solve real-world challenges. Through hands-on projects and case studies, you’ll discover how these patterns fit into various Python applications, from simple scripts to complex systems. Modern Python Insights: The book not only explains design patterns but also integrates Python-specific features, such as decorators, context managers, and type hinting, to make the code cleaner and more Pythonic. Best Practices for Software Design: Beyond just patterns, this book emphasizes writing clean, maintainable code, refactoring legacy systems, and building scalable architectures using design patterns. Who This Book is For: Software Developers looking to deepen their understanding of design patterns and enhance their Python skills. Python Engineers who want to write more efficient, reusable, and maintainable code. Software Architects seeking a structured approach to designing scalable systems with Python. Agile Teams or Scrum Masters who want to integrate design patterns into their development process for better collaboration and system reliability. What You’ll Learn: Creational Patterns like Singleton and Factory Method that simplify object creation. Structural Patterns such as Adapter, Composite, and Decorator that optimize system organization. Behavioral Patterns like Observer and Strategy that manage object interaction. Advanced Patterns like Dependency Injection and Event-Driven Architecture for modern, scalable applications. This book goes beyond theory and empowers you to apply what you've learned in real projects, whether you're building a simple application or developing enterprise-level software. You'll gain the skills to design better systems that are flexible, maintainable, and ready to evolve with your business needs. Hands-On Design Patterns with Python is a practical guide that equips you with everything you need to write cleaner, more efficient, and future-proof software.