Java Basics Using ChatGPT/GPT-4

Java Basics Using ChatGPT/GPT-4 PDF Author: Oswald Campesato
Publisher: Stylus Publishing, LLC
ISBN: 1501518976
Category : Computers
Languages : en
Pages : 534

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Book Description
This book is designed for those new to Java and interested in understanding how ChatGPT/GPT-4 can enhance programming. It offers a unique approach to learning Java, combining traditional hand-written code with cutting-edge ChatGPT-generated examples. The book covers the basics of Java programming and development environments, including understanding recursion, strings, arrays, fundamental data structures, algorithm analysis, queues and stacks, and follows with the role of ChatGPT in generating, explaining, and debugging code. Companion files with source code and figures available for downloading. It’s an essential resource for those starting Java programming and for anyone curious about the applications of ChatGPT in coding. FEATURES Combines hand-crafted Java code with ChatGPT-generated examples for a multifaceted learning experience Offers practical Java coding skills, with examples in recursion, data structures, and algorithm analysis Covers the capabilities of ChatGPT for code generation, debugging, and explanation, providing a modern perspective on programming Includes companion files for downloading with source code and figures

Java Basics Using Chatgpt/Gpt-4

Java Basics Using Chatgpt/Gpt-4 PDF Author: OSWALD. CAMPESATO
Publisher: Walter de Gruyter GmbH & Co KG
ISBN: 1501518917
Category : Computers
Languages : en
Pages : 345

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Book Description
This book is designed for those new to Java and interested in understanding how ChatGPT/GPT-4 can enhance programming. It offers a unique approach to learning Java, combining traditional hand-written code with cutting-edge ChatGPT-generated examples. The book covers the basics of Java programming and development environments, including understanding recursion, strings, arrays, fundamental data structures, algorithm analysis, queues and stacks, and follows with the role of ChatGPT in generating, explaining, and debugging code. Companion files with source code and figures available for downloading. It's an essential resource for those starting Java programming and for anyone curious about the applications of ChatGPT in coding. FEATURES Combines hand-crafted Java code with ChatGPT-generated examples for a multifaceted learning experience Offers practical Java coding skills, with examples in recursion, data structures, and algorithm analysis Covers the capabilities of ChatGPT for code generation, debugging, and explanation, providing a modern perspective on programming Includes companion files for downloading with source code and figures

ChatGPT for Java

ChatGPT for Java PDF Author: Bruce Hopkins
Publisher: Springer Nature
ISBN:
Category :
Languages : en
Pages : 243

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Book Description


Practical Java Programming with ChatGPT

Practical Java Programming with ChatGPT PDF Author: Alan S. Bluck
Publisher: Orange Education Pvt Ltd
ISBN: 8119416791
Category : Computers
Languages : en
Pages : 409

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Book Description
How to use ChatGPT to write fast validated Java code KEY FEATURES ● Discover how to leverage Java code generated with ChatGPT to expedite the development of practical solutions for everyday programming challenges. ● Gain insight into the benefits of harnessing AI to elevate your effectiveness as a software engineer. ● Elevate your professional journey by significantly boosting your programming efficiency to swiftly produce reliable; tested code. ● Harness and validate the potential of ChatGPT; both directly through the ChatGPT Java API and indirectly by leveraging ChatGPT's Java code generation capabilities. DESCRIPTION Embark on a Fascinating Journey into AI-Powered Software Development with ChatGPT. This transformative book challenges the conventional speed of software development by showcasing a diverse array of inquiries directed at cutting-edge AI tools, including Ask AI, ChatGPT 3.5, Perplexity AI, Microsoft Bing Chatbot based on ChatGPT 4.0, and the Phed mobile app. Diving deep into the integration of Java and ChatGPT, this book provides readers with a comprehensive understanding of their synergy in programming. Each carefully crafted question serves as a testament to ChatGPT's exceptional ability to swiftly generate Java programs. The resulting code undergoes rigorous validation using the latest open-source Eclipse IDE and the Java language, empowering readers to craft efficient code in a fraction of the usual time. The journey doesn't end there—this book looks ahead to the promising future of ChatGPT, unveiling exciting potential enhancements planned by OpenAI. These innovations are poised to usher in even more formidable AI-driven capabilities for software development. WHAT WILL YOU LEARN ● Develop NLP Solutions in Java for Mathematical, Content, and Sentiment Analysis. ● Seamlessly Integrate ChatGPT with Java via OpenAI API. ● Harness AI-Powered Code Snippet Generation and Intelligent Code Suggestions. ● Leverage Rapid Idea Prototyping and Validation in Java Development. ● Empower the Creation of Tailored Java Applications. ● Enhance Efficiency and Expedite Prototyping with Instant AI Insights. WHO IS THIS BOOK FOR? This book is tailored for Java Programmers, IT consultants, Systems and Solution Architects with fundamental IT knowledge. It offers practical templates for Java programming solutions, complete with ChatGPT-powered examples. These templates empower Developers working on data processing, mathematical analysis, and document management, facilitating implementations for industries such as Manufacturing, Banking, and Insurance Companies. TABLE OF CONTENTS 1. Getting Started with ChatGPT 2. Java Programming – Best Practices as Stated by ChatGPT 3. Developing Java Code for Utilizing the ChatGPT API 4. Java Program for Using Binary Search 5. Installation of the Latest Open-source Eclipse Java IDE 6. ChatGPT Generated Java Code for Fourier Analysis 7. ChatGPT Generated Java Code for the Fast Fourier Transform 8. ChatGPT Generated Java Code for Indexing a Document 9. ChatGPT-Generated Java Code for Saltikov Particle Distribution 10. ChatGPT-Generated Java Code to Invert a Triangular Matrix 11. ChatGPT Generated Java Code to Store a Document in the IBM FileNet System 12. Conclusions and the Future of ChatGPT for Program Development 13. Appendices for Additional Questions Index

OpenAI GPT For Python Developers - 2nd Edition

OpenAI GPT For Python Developers - 2nd Edition PDF Author: Aymen El Amri
Publisher: Independently Published
ISBN:
Category : Computers
Languages : en
Pages : 0

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Book Description
The knowledge you'll acquire from this guide will be applicable to the current families of GPT models (GPT-3, GPT-3.5, GPT-4, etc.) and will likely also be relevant to GPT-5, should it ever be released. OpenAI provides APIs (Application Programming Interfaces) to access their AI. The goal of an API is to abstract the underlying models by creating a universal interface for all versions, allowing users to use GPT regardless of its version. This guide aims to provide a comprehensive, step-by-step tutorial on how to utilize GPT-3.5 and GPT-4 in your projects via this API. It also covers other models, such as Whisper and Text-to-Speech. If you're developing a chatbot, an AI assistant, or a web application that utilizes AI-generated data, this guide will assist you in achieving your objectives. If you have a basic understanding of the Python programming language and are willing to learn a few additional techniques, such as using Pandas Dataframes and some NLP methods, you possess all the necessary tools to start building intelligent systems with OpenAI tools. Rest assured, you don't need to be a data scientist, machine learning engineer, or AI expert to comprehend and implement the concepts, techniques, and tutorials presented in this guide. The explanations provided are straightforward and easy to understand, featuring simple Python code, examples, and hands-on exercises. This guide emphasizes practical, hands-on learning and is designed to assist readers in building real-world applications. It is example-driven and provides numerous practical examples to help readers understand the concepts and apply them to real-life scenarios to solve real-world problems. By the end of your learning journey, you will have developed applications such as: Fine-tuned, domain-specific chatbots. An intelligent conversational system with memory and context. A semantic modern search engine using RAG and other techniques. An intelligent coffee recommendation system based on your taste. A chatbot assistant to assist with Linux commands A fine-tuned news category prediction system. An AI-to-AI autonomous discussion system to simulate human-like conversations or solve problems An AI-based mental health coach trained on a large dataset of mental health conversations and more! By reading this guide and following the examples, you will be able to: Understand the different models available, and how and when to use each one. Generate human-like text for various purposes, such as answering questions, creating content, and other creative uses. Control the creativity of GPT models and adopt the best practices to generate high-quality text. Transform and edit the text to perform translation, formatting, and other useful tasks. Optimize the performance of GPT models using various parameters and options such as max_tokens, temperature, top_p, n, stream, logprobs, stop, presence_penalty, frequency_penalty, best_of, and others. Stem, lemmatize and reduce your costs when using the API. Understand Context Stuffing, chaining, and practice prompt engineering. Implement a chatbot with memory and context. Create prediction algorithms and zero-shot techniques and evaluate their accuracy. Understand, practice, and improve few-shot learning. Understand fine-tuning and leverage its power to create your own fine-tuned models. Understand and use fine-tuning best practices Practice training and classification techniques using GPT. Understand embedding and how companies such as Tesla and Notion are using it. Understand and implement semantic search, RAG, and other advanced tools and concepts. Integrate a Vector Database (e.g.: Weaviate) with your intelligent systems.

Learning Java

Learning Java PDF Author: Patrick Niemeyer
Publisher: "O'Reilly Media, Inc."
ISBN: 9780596002855
Category : Computers
Languages : en
Pages : 836

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Book Description
This updated edition introduces the basics of Java and everything necessary to get up to speed on the new 1.4 version quickly. CD contains the Java 2 SDK for Windows, Linux and Solaris.

Head First EJB

Head First EJB PDF Author: Kathy Sierra
Publisher: "O'Reilly Media, Inc."
ISBN: 0596005717
Category : Computers
Languages : en
Pages : 733

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Book Description
"Passing the Sun certified business component developer exam"--Cover.

Grokking Deep Learning

Grokking Deep Learning PDF Author: Andrew W. Trask
Publisher: Simon and Schuster
ISBN: 163835720X
Category : Computers
Languages : en
Pages : 475

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Book Description
Summary Grokking Deep Learning teaches you to build deep learning neural networks from scratch! In his engaging style, seasoned deep learning expert Andrew Trask shows you the science under the hood, so you grok for yourself every detail of training neural networks. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology Deep learning, a branch of artificial intelligence, teaches computers to learn by using neural networks, technology inspired by the human brain. Online text translation, self-driving cars, personalized product recommendations, and virtual voice assistants are just a few of the exciting modern advancements possible thanks to deep learning. About the Book Grokking Deep Learning teaches you to build deep learning neural networks from scratch! In his engaging style, seasoned deep learning expert Andrew Trask shows you the science under the hood, so you grok for yourself every detail of training neural networks. Using only Python and its math-supporting library, NumPy, you'll train your own neural networks to see and understand images, translate text into different languages, and even write like Shakespeare! When you're done, you'll be fully prepared to move on to mastering deep learning frameworks. What's inside The science behind deep learning Building and training your own neural networks Privacy concepts, including federated learning Tips for continuing your pursuit of deep learning About the Reader For readers with high school-level math and intermediate programming skills. About the Author Andrew Trask is a PhD student at Oxford University and a research scientist at DeepMind. Previously, Andrew was a researcher and analytics product manager at Digital Reasoning, where he trained the world's largest artificial neural network and helped guide the analytics roadmap for the Synthesys cognitive computing platform. Table of Contents Introducing deep learning: why you should learn it Fundamental concepts: how do machines learn? Introduction to neural prediction: forward propagation Introduction to neural learning: gradient descent Learning multiple weights at a time: generalizing gradient descent Building your first deep neural network: introduction to backpropagation How to picture neural networks: in your head and on paper Learning signal and ignoring noise:introduction to regularization and batching Modeling probabilities and nonlinearities: activation functions Neural learning about edges and corners: intro to convolutional neural networks Neural networks that understand language: king - man + woman == ? Neural networks that write like Shakespeare: recurrent layers for variable-length data Introducing automatic optimization: let's build a deep learning framework Learning to write like Shakespeare: long short-term memory Deep learning on unseen data: introducing federated learning Where to go from here: a brief guide

Learning Processing

Learning Processing PDF Author: Daniel Shiffman
Publisher: Newnes
ISBN: 0123947928
Category : Computers
Languages : en
Pages : 566

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Book Description
Learning Processing, Second Edition, is a friendly start-up guide to Processing, a free, open-source alternative to expensive software and daunting programming languages. Requiring no previous experience, this book is for the true programming beginner. It teaches the basic building blocks of programming needed to create cutting-edge graphics applications including interactive art, live video processing, and data visualization. Step-by-step examples, thorough explanations, hands-on exercises, and sample code, supports your learning curve.A unique lab-style manual, the book gives graphic and web designers, artists, and illustrators of all stripes a jumpstart on working with the Processing programming environment by providing instruction on the basic principles of the language, followed by careful explanations of select advanced techniques. The book has been developed with a supportive learning experience at its core. From algorithms and data mining to rendering and debugging, it teaches object-oriented programming from the ground up within the fascinating context of interactive visual media.This book is ideal for graphic designers and visual artists without programming background who want to learn programming. It will also appeal to students taking college and graduate courses in interactive media or visual computing, and for self-study. - A friendly start-up guide to Processing, a free, open-source alternative to expensive software and daunting programming languages - No previous experience required—this book is for the true programming beginner! - Step-by-step examples, thorough explanations, hands-on exercises, and sample code supports your learning curve

Python Object-Oriented Programming

Python Object-Oriented Programming PDF Author: Steven F. Lott
Publisher: Packt Publishing Ltd
ISBN: 1801075239
Category : Computers
Languages : en
Pages : 715

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Book Description
A comprehensive guide to exploring modern Python through data structures, design patterns, and effective object-oriented techniques Key Features Build an intuitive understanding of object-oriented design, from introductory to mature programs Learn the ins and outs of Python syntax, libraries, and best practices Examine a machine-learning case study at the end of each chapter Book Description Object-oriented programming (OOP) is a popular design paradigm in which data and behaviors are encapsulated in such a way that they can be manipulated together. Python Object-Oriented Programming, Fourth Edition dives deep into the various aspects of OOP, Python as an OOP language, common and advanced design patterns, and hands-on data manipulation and testing of more complex OOP systems. These concepts are consolidated by open-ended exercises, as well as a real-world case study at the end of every chapter, newly written for this edition. All example code is now compatible with Python 3.9+ syntax and has been updated with type hints for ease of learning. Steven and Dusty provide a comprehensive, illustrative tour of important OOP concepts, such as inheritance, composition, and polymorphism, and explain how they work together with Python's classes and data structures to facilitate good design. In addition, the book also features an in-depth look at Python's exception handling and how functional programming intersects with OOP. Two very powerful automated testing systems, unittest and pytest, are introduced. The final chapter provides a detailed discussion of Python's concurrent programming ecosystem. By the end of the book, you will have a thorough understanding of how to think about and apply object-oriented principles using Python syntax and be able to confidently create robust and reliable programs. What you will learn Implement objects in Python by creating classes and defining methods Extend class functionality using inheritance Use exceptions to handle unusual situations cleanly Understand when to use object-oriented features, and more importantly, when not to use them Discover several widely used design patterns and how they are implemented in Python Uncover the simplicity of unit and integration testing and understand why they are so important Learn to statically type check your dynamic code Understand concurrency with asyncio and how it speeds up programs Who this book is for If you are new to object-oriented programming techniques, or if you have basic Python skills and wish to learn how and when to correctly apply OOP principles in Python, this is the book for you. Moreover, if you are an object-oriented programmer coming from other languages or seeking a leg up in the new world of Python, you will find this book a useful introduction to Python. Minimal previous experience with Python is necessary.