Deep Learning with fastai Cookbook: Leverage the easy-to-use fastai framework to unlock the power of deep learning
暫譯: 使用 fastai 的深度學習食譜:利用易於使用的 fastai 框架釋放深度學習的潛力
Ryan, Mark
- 出版商: Packt Publishing
- 出版日期: 2021-09-24
- 售價: $2,000
- 貴賓價: 9.5 折 $1,900
- 語言: 英文
- 頁數: 338
- 裝訂: Quality Paper - also called trade paper
- ISBN: 1800208103
- ISBN-13: 9781800208100
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相關分類:
DeepLearning
海外代購書籍(需單獨結帳)
相關主題
商品描述
Key Features
- Discover how to apply state-of-the-art deep learning techniques to real-world problems
- Build and train neural networks using the power and flexibility of the fastai framework
- Use deep learning to tackle problems such as image classification and text classification
Book 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 learn
- Prepare real-world raw datasets to train fastai deep learning models
- Train fastai deep learning models using text and tabular data
- Create recommender systems with fastai
- Find out how to assess whether fastai is a good fit for a given problem
- Deploy fastai deep learning models in web applications
- Train fastai deep learning models for image classification
Who 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.
商品描述(中文翻譯)
#### 主要特點
- 探索如何將最先進的深度學習技術應用於現實世界的問題
- 使用 fastai 框架的強大與靈活性來構建和訓練神經網絡
- 利用深度學習解決圖像分類和文本分類等問題
#### 書籍描述
fastai 是一個易於使用的深度學習框架,建立在 PyTorch 之上,讓您能夠用少至 10 行代碼快速創建完整的深度學習解決方案。兩個主要的低階深度學習框架,TensorFlow 和 PyTorch,即使在簡單的應用中也需要大量的代碼。相比之下,fastai 為您處理繁瑣的細節,讓您專注於將深度學習應用於實際問題的解決。
本書首先總結了 fastai 的價值,並展示如何使用 fastai 創建一個簡單的「你好,世界」深度學習應用。接著,您將學習如何使用 fastai 處理框架明確支持的四個應用領域:表格數據、文本數據(NLP)、推薦系統和視覺數據。隨著進度的推進,您將通過一系列實用範例,了解如何創建每種類型的現實應用。接下來,您將學習如何部署 fastai 模型,包括創建一個簡單的網頁應用,預測圖像中描繪的物體。本書最後將概述 fastai 的進階功能。
在閱讀完這本 fastai 書籍後,您將能夠使用 fastai 創建自己的深度學習應用。您還將學會如何使用 fastai 準備原始數據集、探索數據集、訓練深度學習模型以及部署訓練好的模型。
#### 您將學到什麼
- 準備現實世界的原始數據集以訓練 fastai 深度學習模型
- 使用文本和表格數據訓練 fastai 深度學習模型
- 使用 fastai 創建推薦系統
- 瞭解如何評估 fastai 是否適合特定問題
- 在網頁應用中部署 fastai 深度學習模型
- 訓練 fastai 深度學習模型以進行圖像分類
#### 本書適合誰
本書適合數據科學家、機器學習開發者和希望通過食譜式方法探索 fastai 框架的深度學習愛好者。建議具備 Python 程式語言的工作知識和機器學習基礎,以便充分利用這本深度學習書籍。
作者簡介
Mark Ryan is a machine learning practitioner and technology manager who is passionate about delivering end-to-end deep learning applications that solve real-world problems. Mark has worked on deep learning projects that incorporate a variety of related technologies, including Rasa chatbots, web applications, and messenger platforms. As a strong believer in democratizing technology, Mark advocates for Keras and fastai as accessible frameworks that open up deep learning to non-specialists. Mark has a degree in computer science from the University of Waterloo and a Master of Science degree in computer science from the University of Toronto.
作者簡介(中文翻譯)
馬克·瑞安是一位機器學習實踐者和技術經理,熱衷於提供端到端的深度學習應用,以解決現實世界中的問題。馬克曾參與多個深度學習項目,這些項目結合了各種相關技術,包括 Rasa 聊天機器人、網頁應用程式和即時通訊平台。作為一位堅信技術應該普及化的倡導者,馬克提倡使用 Keras 和 fastai 作為可接觸的框架,讓非專業人士也能進入深度學習的領域。馬克擁有滑鐵盧大學的計算機科學學位,以及多倫多大學的計算機科學碩士學位。
目錄大綱
- Getting Started with fastai
- Exploring and Cleaning Up Data with fastai
- Training Models with Tabular Data
- Training Models with Text Data
- Training Recommender Systems
- Training Models with Visual Data
- Deployment and Model Maintenance
- Extended fastai and Deployment Features
目錄大綱(中文翻譯)
- Getting Started with fastai
- Exploring and Cleaning Up Data with fastai
- Training Models with Tabular Data
- Training Models with Text Data
- Training Recommender Systems
- Training Models with Visual Data
- Deployment and Model Maintenance
- Extended fastai and Deployment Features