Exploring The Python Library Ecosystem
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Exploring The Python Library Ecosystem
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Author : Frahaan Hussain
language : en
Publisher:
Release Date : 2023-11-09
Exploring The Python Library Ecosystem written by Frahaan Hussain and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-11-09 with categories.
"Exploring the Python Library Ecosystem: A Comprehensive Guide" is your essential companion on a journey through the rich and diverse world of Python libraries. Whether you're a beginner looking to harness the power of Python for the first time or an experienced developer seeking to expand your toolkit, this comprehensive guide offers valuable insights and hands-on knowledge to help you make the most of Python's extensive library ecosystem. Inside this book, you'll delve into the heart of Python development, uncovering a vast array of libraries and modules that can streamline your projects, boost productivity, and supercharge your code. From data science and web development to software engineering and beyond, Python libraries play a pivotal role in nearly every aspect of modern programming. Key highlights include: A curated selection of essential Python libraries for various programming domains. Practical examples and use cases to illustrate how each library can be applied. Hands-on tutorials to help you master the fundamentals of using Python libraries effectively. Tips and best practices for optimizing your development workflow. Guidance on selecting the right libraries for your specific projects. Expert insights into the Python library ecosystem's latest trends and updates. "Exploring the Python Library Ecosystem" empowers you to harness the full potential of Python by tapping into the wealth of resources available within its library ecosystem. Whether you're a data scientist, web developer, or software engineer, this book provides the knowledge and tools you need to excel in your Python programming endeavors.
Python Projects
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Author : Laura Cassell
language : en
Publisher: John Wiley & Sons
Release Date : 2014-12-03
Python Projects written by Laura Cassell and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-12-03 with Computers categories.
A guide to completing Python projects for those ready to take their skills to the next level Python Projects is the ultimate resource for the Python programmer with basic skills who is ready to move beyond tutorials and start building projects. The preeminent guide to bridge the gap between learning and doing, this book walks readers through the "where" and "how" of real-world Python programming with practical, actionable instruction. With a focus on real-world functionality, Python Projects details the ways that Python can be used to complete daily tasks and bring efficiency to businesses and individuals alike. Python Projects is written specifically for those who know the Python syntax and lay of the land, but may still be intimidated by larger, more complex projects. The book provides a walk-through of the basic set-up for an application and the building and packaging for a library, and explains in detail the functionalities related to the projects. Topics include: *How to maximize the power of the standard library modules *Where to get third party libraries, and the best practices for utilization *Creating, packaging, and reusing libraries within and across projects *Building multi-layered functionality including networks, data, and user interfaces *Setting up development environments and using virtualenv, pip, and more Written by veteran Python trainers, the book is structured for easy navigation and logical progression that makes it ideal for individual, classroom, or corporate training. For Python developers looking to apply their skills to real-world challenges, Python Projects is a goldmine of information and expert insight.
Machine Learning And Deep Learning Using Python And Tensorflow
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Author : Venkata Reddy Konasani
language : en
Publisher: McGraw Hill Professional
Release Date : 2021-04-29
Machine Learning And Deep Learning Using Python And Tensorflow written by Venkata Reddy Konasani and has been published by McGraw Hill Professional this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-04-29 with Technology & Engineering categories.
Understand the principles and practices of machine learning and deep learning This hands-on guide lays out machine learning and deep learning techniques and technologies in a style that is approachable, using just the basic math required. Written by a pair of experts in the field, Machine Learning and Deep Learning Using Python and TensorFlow contains case studies in several industries, including banking, insurance, e-commerce, retail, and healthcare. The book shows how to utilize machine learning and deep learning functions in today’s smart devices and apps. You will get download links for datasets, code, and sample projects referred to in the text. Coverage includes: Machine learning and deep learning concepts Python programming and statistics fundamentals Regression and logistic regression Decision trees Model selection and cross-validation Cluster analysis Random forests and boosting Artificial neural networks TensorFlow and Keras Deep learning hyperparameters Convolutional neural networks Recurrent neural networks and long short-term memory
Deep Learning With Jax
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Author : Grigory Sapunov
language : en
Publisher: Simon and Schuster
Release Date : 2024-12-03
Deep Learning With Jax written by Grigory Sapunov and has been published by Simon and Schuster this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-03 with Computers categories.
Accelerate deep learning and other number-intensive tasks with JAX, Google’s awesome high-performance numerical computing library. The JAX numerical computing library tackles the core performance challenges at the heart of deep learning and other scientific computing tasks. By combining Google’s Accelerated Linear Algebra platform (XLA) with a hyper-optimized version of NumPy and a variety of other high-performance features, JAX delivers a huge performance boost in low-level computations and transformations. In Deep Learning with JAX you will learn how to: • Use JAX for numerical calculations • Build differentiable models with JAX primitives • Run distributed and parallelized computations with JAX • Use high-level neural network libraries such as Flax • Leverage libraries and modules from the JAX ecosystem Deep Learning with JAX is a hands-on guide to using JAX for deep learning and other mathematically-intensive applications. Google Developer Expert Grigory Sapunov steadily builds your understanding of JAX’s concepts. The engaging examples introduce the fundamental concepts on which JAX relies and then show you how to apply them to real-world tasks. You’ll learn how to use JAX’s ecosystem of high-level libraries and modules, and also how to combine TensorFlow and PyTorch with JAX for data loading and deployment. About the technology Google’s JAX offers a fresh vision for deep learning. This powerful library gives you fine control over low level processes like gradient calculations, delivering fast and efficient model training and inference, especially on large datasets. JAX has transformed how research scientists approach deep learning. Now boasting a robust ecosystem of tools and libraries, JAX makes evolutionary computations, federated learning, and other performance-sensitive tasks approachable for all types of applications. About the book Deep Learning with JAX teaches you to build effective neural networks with JAX. In this example-rich book, you’ll discover how JAX’s unique features help you tackle important deep learning performance challenges, like distributing computations across a cluster of TPUs. You’ll put the library into action as you create an image classification tool, an image filter application, and other realistic projects. The nicely-annotated code listings demonstrate how JAX’s functional programming mindset improves composability and parallelization. What's inside • Use JAX for numerical calculations • Build differentiable models with JAX primitives • Run distributed and parallelized computations with JAX • Use high-level neural network libraries such as Flax About the reader For intermediate Python programmers who are familiar with deep learning. About the author Grigory Sapunov holds a Ph.D. in artificial intelligence and is a Google Developer Expert in Machine Learning. The technical editor on this book was Nicholas McGreivy. Table of Contents Part 1 1 When and why to use JAX 2 Your first program in JAX Part 2 3 Working with arrays 4 Calculating gradients 5 Compiling your code 6 Vectorizing your code 7 Parallelizing your computations 8 Using tensor sharding 9 Random numbers in JAX 10 Working with pytrees Part 3 11 Higher-level neural network libraries 12 Other members of the JAX ecosystem A Installing JAX B Using Google Colab C Using Google Cloud TPUs D Experimental parallelization
Core Python Applications Programming
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Author : Wesley Chun
language : en
Publisher: Prentice Hall
Release Date : 2012
Core Python Applications Programming written by Wesley Chun and has been published by Prentice Hall this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012 with Computers categories.
Rev. ed. of: Core Python programming / Wesley J. Chun. c2007.
Library Mashups
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Author : Nicole C. Engard
language : en
Publisher: Information Today, Inc.
Release Date : 2009
Library Mashups written by Nicole C. Engard and has been published by Information Today, Inc. this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009 with Computers categories.
"This unique book is geared to help any library keep its website dynamically and collaboratively up-to-date, increase user participation, and provide exemplary web-based service through the power of mashups."--Back cover.
Tanmay Teaches Go The Ideal Language For Backend Developers
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Author : Tanmay Bakshi
language : en
Publisher: McGraw Hill Professional
Release Date : 2021-05-28
Tanmay Teaches Go The Ideal Language For Backend Developers written by Tanmay Bakshi and has been published by McGraw Hill Professional this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-05-28 with Computers categories.
Write your own efficient, performant, and lightweight programs using Go Quickly start developing your own Google Go programs using the practical information contained in this engaging resource. Social media personalities Tanmay Bakshi and Baheer Kamal show, step by step, how to develop custom applications that fully utilize Go’s lightweight runtime and concurrency features. Tanmay Teaches Go: The Ideal Language for Backend Developers teaches by doing. This book guides you through the development and programming processes and features detailed examples, code samples, and time-saving tips. Inside, you’ll learn to: Install Go on Windows, Linux, or macOS devices Get up and running with writing your own Go apps Define variables and use them in your programs Work with statements, functions, loops, and arrays Use Go modules to simplify program development Utilize built-in and third-party packages Write custom packages that fit your programming needs Understand classic structures and algorithms Improve performance using Go routines and concurrency Import external code—even code not written in Go!
Library Journal
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Author :
language : en
Publisher:
Release Date : 1996
Library Journal written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1996 with Libraries categories.
Includes, beginning Sept. 15, 1954 (and on the 15th of each month, Sept.-May) a special section: School library journal, ISSN 0000-0035, (called Junior libraries, 1954-May 1961). Also issued separately.
Python In Depth
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Author : Nathan Venture, D
language : en
Publisher: eBookIt.com
Release Date : 2024-08-19
Python In Depth written by Nathan Venture, D and has been published by eBookIt.com this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-08-19 with Computers categories.
Step Into the Future of Coding with Python: Your Comprehensive Guide Awaits Dive into the vibrant universe of Python and emerge as a skilled coder and programmer equipped with the knowledge to tackle any challenge the digital world throws your way. Python in Depth: A Multipurpose Coder and Programmer's Guide is not just another programming book; it's a beacon guiding you through the ever-evolving landscape of Python, from basic concepts to the most advanced applications. Begin your journey with an insightful introduction that not only welcomes you to the Python community but also prepares you for the exciting path ahead. Explore the world of Python in our first chapter, understanding why Python's simplicity and versatility make it the go-to language for professionals worldwide. Whether you're setting up your environment, selecting an IDE, or diving into Python's syntax and structure, this guide ensures a smooth initiation into coding practices that matter. But that's just the start.As you progress, immerse yourself in intermediate and advanced topics that are crucial for modern development. From object-oriented programming, exception handling, to exploring Python's extensive library ecosystem, every chapter serves as a stepping stone towards mastery. Delve into databases, web frameworks like Django and Flask, and unlock the potential of Python in data science, machine learning, and beyond. What truly sets this guide apart is its dedication to not just teaching Python, but doing so in a manner that promotes readability, efficiency, and best practices. Learn how to optimize your code, adhere to the Python style guide, and navigate the nuances of collaborative development with ease. By the end of this comprehensive guide, you will not only have a deep understanding of Python's core concepts but also have the skills to apply them in real-world scenarios - from web development and data analysis to networking, security, and even creative coding. Whether you're a complete beginner or looking to expand your knowledge, Python in Depth: A Multipurpose Coder and Programmer's Guide is the key to unlocking your full potential in today's tech-driven world. Embark on this transformative journey through Python and ready yourself for a future where the possibilities are limitless. It's time to code, create, and innovate. Let's get started.
Introduction To Machine Learning With Python
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Author : Ahmed Alabadla
language : en
Publisher: Independently Published
Release Date : 2025-10-03
Introduction To Machine Learning With Python written by Ahmed Alabadla and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-10-03 with Computers categories.
Introduction to Machine Learning with Python: A Practical Guide for Beginners is the ultimate resource for anyone who wants to understand the core concepts of artificial intelligence and apply them using Python. Designed for beginners and self-learners, this book provides a step-by-step journey through the world of machine learning, combining theoretical foundations with hands-on coding practice. From the first chapter, readers are introduced to the fundamentals of machine learning, its different types, and how Python has become the most powerful tool for AI development. You will learn how to set up your machine learning environment, explore the Python ecosystem, and understand ethical considerations when working with AI systems. The book moves into Python basics for machine learning, covering essential programming skills, control structures, and the most important libraries for data science and AI, including NumPy, Pandas, Matplotlib, and Scikit-learn. These tools form the backbone of modern machine learning, enabling you to handle data, create visualizations, and implement algorithms with ease. Data is the heart of every AI system, and this book dedicates a section to data preprocessing and exploration. Readers will discover how to clean and prepare data, manage missing values, detect outliers, and perform exploratory data analysis (EDA). With the help of visualizations powered by Matplotlib and Python's data-handling techniques, you will learn how to shape raw datasets into high-quality inputs for machine learning models. Next, the book dives into supervised learning. Starting with linear regression and decision trees, you will progress to advanced algorithms such as Support Vector Machines and kernel functions. Each concept is explained in simple terms, followed by practical machine learning projects to reinforce your understanding. By the end of this section, you will be confident in applying supervised learning techniques to real-world problems. The journey continues with unsupervised learning, where you will explore clustering algorithms, dimensionality reduction, and anomaly detection. These techniques allow you to uncover hidden patterns, reduce complexity, and identify unusual behaviors in datasets. With hands-on applications, you will see how unsupervised learning can be used in industries ranging from healthcare and finance to marketing and cybersecurity. Unlike many overly technical books, this guide balances theory and practice. Each topic is supported by clear explanations, coding exercises, and applied examples. Whether you are a student, researcher, or professional, this book will give you the foundation to understand how AI systems work and the confidence to build your own models. By the time you finish, you will have mastered: The fundamentals of machine learning with Python. Essential Python tools and libraries: NumPy, Pandas, Matplotlib, Scikit-learn. Data preprocessing, including handling missing data and detecting outliers. Supervised learning algorithms: Linear Regression, Decision Trees, Support Vector Machines. Unsupervised learning methods: Clustering, Dimensionality Reduction, Anomaly Detection. Real-world applications through applied machine learning techniques and projects. Whether your goal is to enter data science, enhance your career with AI skills, or simply gain a deeper understanding of machine learning, this book provides the roadmap you need. It bridges the gap between theory and application, making Introduction to Machine Learning with Python an essential companion for anyone ready to explore the future of artificial intelligence.