Deep Learning For Coders With Fastai And Pytorch

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Deep Learning For Coders With Fastai And Pytorch

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Author : Jeremy Howard
language : en
Publisher: O'Reilly Media
Release Date : 2020-06-29

Deep Learning For Coders With Fastai And Pytorch written by Jeremy Howard and has been published by O'Reilly Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-06-29 with Computers categories.

Deep learning is often viewed as the exclusive domain of math PhDs and big tech companies. But as this hands-on guide demonstrates, programmers comfortable with Python can achieve impressive results in deep learning with little math background, small amounts of data, and minimal code. How? With fastai, the first library to provide a consistent interface to the most frequently used deep learning applications. Authors Jeremy Howard and Sylvain Gugger, the creators of fastai, show you how to train a model on a wide range of tasks using fastai and PyTorch. You’ll also dive progressively further into deep learning theory to gain a complete understanding of the algorithms behind the scenes. Train models in computer vision, natural language processing, tabular data, and collaborative filtering Learn the latest deep learning techniques that matter most in practice Improve accuracy, speed, and reliability by understanding how deep learning models work Discover how to turn your models into web applications Implement deep learning algorithms from scratch Consider the ethical implications of your work Gain insight from the foreword by PyTorch cofounder, Soumith Chintala

Deep Learning For Coders With Fastai Pytorch

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Author : Jeremy Howard (Scientist)
language : en
Publisher:
Release Date : 2021

Deep Learning For Coders With Fastai Pytorch written by Jeremy Howard (Scientist) and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021 with Artificial intelligence categories.

Deep Learning With Fastai Cookbook

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Author : Mark Ryan
language : en
Publisher: Packt Publishing Ltd
Release Date : 2021-09-24

Deep Learning With Fastai Cookbook written by Mark Ryan and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-09-24 with Computers categories.

Harness the power of the easy-to-use, high-performance fastai framework to rapidly create complete deep learning solutions with few lines of code Key FeaturesDiscover how to apply state-of-the-art deep learning techniques to real-world problemsBuild and train neural networks using the power and flexibility of the fastai frameworkUse deep learning to tackle problems such as image classification and text classificationBook Description fastai is an easy-to-use deep learning framework built on top of PyTorch that lets you rapidly create complete deep learning solutions with as few as 10 lines of code. Both predominant low-level deep learning frameworks, TensorFlow and PyTorch, require a lot of code, even for straightforward applications. In contrast, fastai handles the messy details for you and lets you focus on applying deep learning to actually solve problems. The book begins by summarizing the value of fastai and showing you how to create a simple 'hello world' deep learning application with fastai. You'll then learn how to use fastai for all four application areas that the framework explicitly supports: tabular data, text data (NLP), recommender systems, and vision data. As you advance, you'll work through a series of practical examples that illustrate how to create real-world applications of each type. Next, you'll learn how to deploy fastai models, including creating a simple web application that predicts what object is depicted in an image. The book wraps up with an overview of the advanced features of fastai. By the end of this fastai book, you'll be able to create your own deep learning applications using fastai. You'll also have learned how to use fastai to prepare raw datasets, explore datasets, train deep learning models, and deploy trained models. What you will learnPrepare real-world raw datasets to train fastai deep learning modelsTrain fastai deep learning models using text and tabular dataCreate recommender systems with fastaiFind out how to assess whether fastai is a good fit for a given problemDeploy fastai deep learning models in web applicationsTrain fastai deep learning models for image classificationWho this book is for This book is for data scientists, machine learning developers, and deep learning enthusiasts looking to explore the fastai framework using a recipe-based approach. Working knowledge of the Python programming language and machine learning basics is strongly recommended to get the most out of this deep learning book.

Pytorch Pocket Reference

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Author : Joe Papa
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2021-05-11

Pytorch Pocket Reference written by Joe Papa and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-05-11 with Computers categories.

This concise, easy-to-use reference puts one of the most popular frameworks for deep learning research and development at your fingertips. Author Joe Papa provides instant access to syntax, design patterns, and code examples to accelerate your development and reduce the time you spend searching for answers. Research scientists, machine learning engineers, and software developers will find clear, structured PyTorch code that covers every step of neural network development-from loading data to customizing training loops to model optimization and GPU/TPU acceleration. Quickly learn how to deploy your code to production using AWS, Google Cloud, or Azure and deploy your ML models to mobile and edge devices. Learn basic PyTorch syntax and design patterns Create custom models and data transforms Train and deploy models using a GPU and TPU Train and test a deep learning classifier Accelerate training using optimization and distributed training Access useful PyTorch libraries and the PyTorch ecosystem

Coding With Ai For Dummies

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Author : Chris Minnick
language : en
Publisher: John Wiley & Sons
Release Date : 2024-02-23

Coding With Ai For Dummies written by Chris Minnick 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 2024-02-23 with Computers categories.

Boost your coding output and accuracy with artificial intelligence tools Coding with AI For Dummies introduces you to the many ways that artificial intelligence can make your life as a coder easier. Even if you’re brand new to using AI, this book will show you around the new tools that can produce, examine, and fix code for you. With AI, you can automate processes like code documentation, debugging, updating, and optimization. The time saved thanks to AI lets you focus on the core development tasks that make you even more valuable. Learn the secrets behind coding assistant platforms and get step-by-step instructions on how to implement them to make coding a smoother process. Thanks to AI and this Dummies guide, you’ll be coding faster and better in no time. Discover all the core coding tasks boosted by artificial intelligence Meet the top AI coding assistance platforms currently on the market Learn how to generate documentation with AI and use AI to keep your code up to date Use predictive tools to help speed up the coding process and eliminate bugs This is a great Dummies guide for new and experienced programmers alike. Get started with AI coding and expand your programming toolkit with Coding with AI For Dummies.

Python Simplified With Generative Ai

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Author : Duc T. Haba
language : en
Publisher: BPB Publications
Release Date : 2025-04-25

Python Simplified With Generative Ai written by Duc T. Haba and has been published by BPB Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-25 with Computers categories.

DESCRIPTION GenAI and Python are changing how we use technology, making it essential to understand both to stay innovative and work efficiently. GenAI significantly impacts learning Python by generating personalized code snippets, accelerating the learning process. This book bridges the gap between traditional education and the practical challenges students encounter today. It combines hands-on learning with modern GenAI tools like GPT-4 and Copilot. The book begins with fundamental GenAI concepts, including GPT-4 and Gemini, and mastering prompt engineering for optimal GenAI interaction. Instead of starting with technical details like algorithms and syntax, it introduces coding through interactive, practical Python Jupyter Notebooks and Google Colab projects. Readers will learn Python code with a calculator application, explore fundamental sorting algorithms, and manipulate data using Pandas. The book then explores advanced ML through CNN image classification with Fast.ai, and deploying AI models as web applications using Hugging Face and Gradio. It also addresses critical ethical considerations in AI, focusing on fairness and bias, and provides career guidance for modern programmers. Moreover, this book takes a fresh approach to learning by prioritizing exploration and creativity, much like the way Gen Z engage with games, apps, and hands-on activities. By the end of this book, you will be equipped with the practical skills and ethical understanding to confidently apply Python and GenAI in diverse projects, helping you navigate the evolving landscape of AI-driven development. WHAT YOU WILL LEARN ● Write and debug Python code through hands-on projects. ● Learn GenAI setup, and effective prompt engineering. ● Step-by-step Python projects using Jupyter Notebooks and GenAI. ● Deploy AI models as interactive web applications using Hugging Face and Gradio frameworks. ● Leverage GenAI tools like GPT-4 and Copilot. ● Understand AI bias and use it responsibly for positive impact. WHO THIS BOOK IS FOR This book is for professionals interested in learning Python and using GenAI tools like GPT-4 in practical applications. It is for aspiring programmers, students, and data analysts seeking practical Python and GenAI skills. TABLE OF CONTENTS 1. Introduction to GenAI 2. Jupyter Notebook 3. Dissect The Calculator App 4. Sorting on My Mind 5. Pandas, the Data Tamer 6. Decipher CNN App 7. Gradio and Hugging Face Deployment 8. Fairness and Bias 9. Your Turn to Be a Code Walker

Deep Learning With Structured Data

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Author : Mark Ryan
language : en
Publisher: Manning
Release Date : 2020-12-29

Deep Learning With Structured Data written by Mark Ryan and has been published by Manning this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-12-29 with Computers categories.

Deep Learning with Structured Data teaches you powerful data analysis techniques for tabular data and relational databases. Summary Deep learning offers the potential to identify complex patterns and relationships hidden in data of all sorts. Deep Learning with Structured Data shows you how to apply powerful deep learning analysis techniques to the kind of structured, tabular data you'll find in the relational databases that real-world businesses depend on. Filled with practical, relevant applications, this book teaches you how deep learning can augment your existing machine learning and business intelligence systems. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology Here’s a dirty secret: Half of the time in most data science projects is spent cleaning and preparing data. But there’s a better way: Deep learning techniques optimized for tabular data and relational databases deliver insights and analysis without requiring intense feature engineering. Learn the skills to unlock deep learning performance with much less data filtering, validating, and scrubbing. About the book Deep Learning with Structured Data teaches you powerful data analysis techniques for tabular data and relational databases. Get started using a dataset based on the Toronto transit system. As you work through the book, you’ll learn how easy it is to set up tabular data for deep learning, while solving crucial production concerns like deployment and performance monitoring. What's inside When and where to use deep learning The architecture of a Keras deep learning model Training, deploying, and maintaining models Measuring performance About the reader For readers with intermediate Python and machine learning skills. About the author Mark Ryan is a Data Science Manager at Intact Insurance. He holds a Master's degree in Computer Science from the University of Toronto. Table of Contents 1 Why deep learning with structured data? 2 Introduction to the example problem and Pandas dataframes 3 Preparing the data, part 1: Exploring and cleansing the data 4 Preparing the data, part 2: Transforming the data 5 Preparing and building the model 6 Training the model and running experiments 7 More experiments with the trained model 8 Deploying the model 9 Recommended next steps

16th International Conference On Applications Of Fuzzy Systems Soft Computing And Artificial Intelligence Tools Icafs 2023

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Author : Rafik A. Aliev
language : en
Publisher: Springer Nature
Release Date : 2025-02-12

16th International Conference On Applications Of Fuzzy Systems Soft Computing And Artificial Intelligence Tools Icafs 2023 written by Rafik A. Aliev and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-12 with Computers categories.

This book covers diverse areas of fuzzy logic, soft computing, and AI approaches such as uncertain computation, decision-making under imperfect information, deep learning, and others. The topics of the papers include theory and application of soft computing, decision theory with imperfect information, neuro-fuzzy technology, intelligent control, machine learning, evolutionary computing, fuzzy logic, and soft computing in engineering, industry, social sciences, business, economics, earth sciences, material sciences, and others. This book presents the proceedings of the 16th International Conference on Applications of Fuzzy Systems, Soft Computing, and Artificial Intelligence Tools, ICAFS-2023, held in Antalya, Turkey, on September 14–15, 2023. This will be a useful guide for academics, practitioners, and graduates in fields of fuzzy systems and soft computing. It would allow for attracting of interest in development and applying of these paradigms in various real fields.

Hands On Generative Ai With Transformers And Diffusion Models

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Author : Omar Sanseviero
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2024-11-22

Hands On Generative Ai With Transformers And Diffusion Models written by Omar Sanseviero and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-11-22 with Computers categories.

Learn to use generative AI techniques to create novel text, images, audio, and even music with this practical, hands-on book. Readers will understand how state-of-the-art generative models work, how to fine-tune and adapt them to their needs, and how to combine existing building blocks to create new models and creative applications in different domains. This go-to book introduces theoretical concepts followed by guided practical applications, with extensive code samples and easy-to-understand illustrations. You'll learn how to use open source libraries to utilize transformers and diffusion models, conduct code exploration, and study several existing projects to help guide your work. Build and customize models that can generate text and images Explore trade-offs between using a pretrained model and fine-tuning your own model Create and utilize models that can generate, edit, and modify images in any style Customize transformers and diffusion models for multiple creative purposes Train models that can reflect your own unique style

Hands On Machine Learning With Scikit Learn Keras And Tensorflow

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Author : Aurélien Géron
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2022-10-04

Hands On Machine Learning With Scikit Learn Keras And Tensorflow written by Aurélien Géron and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-10-04 with Computers categories.

Through a recent series of breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This bestselling book uses concrete examples, minimal theory, and production-ready Python frameworks (Scikit-Learn, Keras, and TensorFlow) to help you gain an intuitive understanding of the concepts and tools for building intelligent systems. With this updated third edition, author Aurélien Géron explores a range of techniques, starting with simple linear regression and progressing to deep neural networks. Numerous code examples and exercises throughout the book help you apply what you've learned. Programming experience is all you need to get started. Use Scikit-learn to track an example ML project end to end Explore several models, including support vector machines, decision trees, random forests, and ensemble methods Exploit unsupervised learning techniques such as dimensionality reduction, clustering, and anomaly detection Dive into neural net architectures, including convolutional nets, recurrent nets, generative adversarial networks, autoencoders, diffusion models, and transformers Use TensorFlow and Keras to build and train neural nets for computer vision, natural language processing, generative models, and deep reinforcement learning