The Deep Learning Workshop: Take a hands-on approach to understanding deep learning and build smart applications that can recognize images and int
暫譯: 深度學習工作坊:實作理解深度學習並構建能夠識別圖像和文本的智能應用程式
Baig, Mirza Rahim, Joseph, Thomas V., Sadvilkar, Nipun
- 出版商: Packt Publishing
- 出版日期: 2020-07-30
- 售價: $1,830
- 貴賓價: 9.5 折 $1,739
- 語言: 英文
- 頁數: 474
- 裝訂: Quality Paper - also called trade paper
- ISBN: 1839219858
- ISBN-13: 9781839219856
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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
- Understand how to implement deep learning with TensorFlow and Keras
- Learn the fundamentals of computer vision and image recognition
- Study the architecture of different neural networks
Book Description
Are you fascinated by how deep learning powers intelligent applications such as self-driving cars, virtual assistants, facial recognition devices, and chatbots to process data and solve complex problems? Whether you are familiar with machine learning or are new to this domain, The Deep Learning Workshop will make it easy for you to understand deep learning with the help of interesting examples and exercises throughout.
The book starts by highlighting the relationship between deep learning, machine learning, and artificial intelligence and helps you get comfortable with the TensorFlow 2.0 programming structure using hands-on exercises. You'll understand neural networks, the structure of a perceptron, and how to use TensorFlow to create and train models. The book will then let you explore the fundamentals of computer vision by performing image recognition exercises with convolutional neural networks (CNNs) using Keras. As you advance, you'll be able to make your model more powerful by implementing text embedding and sequencing the data using popular deep learning solutions. Finally, you'll get to grips with bidirectional recurrent neural networks (RNNs) and build generative adversarial networks (GANs) for image synthesis.
By the end of this deep learning book, you'll have learned the skills essential for building deep learning models with TensorFlow and Keras.
What you will learn
- Understand how deep learning, machine learning, and artificial intelligence are different
- Develop multilayer deep neural networks with TensorFlow
- Implement deep neural networks for multiclass classification using Keras
- Train CNN models for image recognition
- Handle sequence data and use it in conjunction with RNNs
- Build a GAN to generate high-quality synthesized images
Who this book is for
If you are interested in machine learning and want to create and train deep learning models using TensorFlow and Keras, this workshop is for you. A solid understanding of Python and its packages, along with basic machine learning concepts, will help you to learn the topics quickly.
商品描述(中文翻譯)
#### 主要特點
- 了解如何使用 TensorFlow 和 Keras 實現深度學習
- 學習計算機視覺和圖像識別的基本原理
- 研究不同神經網絡的架構
#### 書籍描述
你是否對深度學習如何驅動智能應用程序(如自駕車、虛擬助手、面部識別設備和聊天機器人)以處理數據和解決複雜問題感到著迷?無論你對機器學習是否熟悉,《深度學習工作坊》都將通過有趣的範例和練習,讓你輕鬆理解深度學習。
本書首先強調深度學習、機器學習和人工智慧之間的關係,並通過實作練習幫助你熟悉 TensorFlow 2.0 的編程結構。你將了解神經網絡、感知器的結構,以及如何使用 TensorFlow 創建和訓練模型。接著,本書將讓你通過使用 Keras 的卷積神經網絡(CNN)進行圖像識別練習,探索計算機視覺的基本原理。隨著進展,你將能夠通過實現文本嵌入和使用流行的深度學習解決方案對數據進行排序,來增強你的模型的能力。最後,你將掌握雙向遞歸神經網絡(RNN)並構建生成對抗網絡(GAN)以進行圖像合成。
在這本深度學習書籍結束時,你將學會使用 TensorFlow 和 Keras 建立深度學習模型所需的技能。
#### 你將學到什麼
- 了解深度學習、機器學習和人工智慧之間的區別
- 使用 TensorFlow 開發多層深度神經網絡
- 使用 Keras 實現多類別分類的深度神經網絡
- 訓練 CNN 模型進行圖像識別
- 處理序列數據並與 RNN 結合使用
- 構建 GAN 以生成高品質的合成圖像
#### 本書適合誰
如果你對機器學習感興趣,並希望使用 TensorFlow 和 Keras 創建和訓練深度學習模型,那麼這個工作坊適合你。對 Python 及其套件有扎實的理解,以及基本的機器學習概念,將幫助你快速學習這些主題。
作者簡介
Mirza Rahim Baig is an avid problem solver who uses deep learning and AI to solve business problems and create impact. A BITS, Pilani graduate, Rahim is a lead at Flipkart, India's largest e-commerce platform. He has a decade of experience in creating value from data, harnessing the power of the latest in Machine learning and AI. Rahim is also a teacher - designing, creating, teaching data science for various learning platforms. He loves making the complex easy to understand.
Thomas V. Joseph is a data science practitioner, researcher, trainer, mentor, and writer with more than 19 years of experience. He has extensive experience in solving business problems using machine learning tool sets across multiple industry segments.
Nipun Sadvilkar is a senior data scientist at US healthcare company leading a team of data scientists and subject matter expertise to design and build the clinical NLP engine to revamp medical coding workflows, enhance coder efficiency, and accelerate revenue cycle. He has experience of more than 3 years in building NLP solutions and web-based data science platforms in the area of healthcare, finance, media, and psychology. His interests lie at the intersection of machine learning and software engineering with a fair understanding of the business domain. He is a member of the regional and national python community. He is author of pySBD - an NLP open-source python library for sentence segmentation which is recognized by ExplosionAI (spaCy) and AllenAI (scispaCy) organizations.
Mohan Kumar Silaparasetty is seasoned deep learning and AI professional. He is a graduate from IIT Kharagpur with more than 25 years of industry experience in a variety of roles. After having a successful corporate career, Mohan embarked on his entrepreneurial journey and is the co-founder and CEO of Trendwise Analytics. This company provides consulting and training in AI and deep learning. He is also the organizer of the Bangalore Artificial intelligence Meetup group with over 3500 members.
Anthony So is an outstanding leader with more than 13 years of experience. He is recognized for his analytical skills and data-driven approach for solving complex business problems and driving performance improvements. He is also a successful coach and mentor with capabilities in statistical analysis and expertise in machine learning with Python.
作者簡介(中文翻譯)
**Mirza Rahim Baig** 是一位熱衷於解決問題的專家,他利用深度學習和人工智慧來解決商業問題並創造影響。Rahim 是比爾拉科技學院(BITS, Pilani)的畢業生,目前擔任印度最大電子商務平台 Flipkart 的領導者。他在從數據中創造價值方面擁有十年的經驗,善用最新的機器學習和人工智慧技術。Rahim 也是一位教師,為各種學習平台設計、創建和教授數據科學課程。他喜歡將複雜的概念簡化為易於理解的內容。
**Thomas V. Joseph** 是一位數據科學實踐者、研究員、培訓師、導師和作家,擁有超過 19 年的經驗。他在使用機器學習工具集解決多個行業的商業問題方面擁有豐富的經驗。
**Nipun Sadvilkar** 是美國一家醫療保健公司的高級數據科學家,領導一支數據科學家和主題專家的團隊,設計並構建臨床自然語言處理(NLP)引擎,以改進醫療編碼工作流程、提高編碼效率並加速收入循環。他在醫療、金融、媒體和心理學領域擁有超過 3 年的 NLP 解決方案和基於網絡的數據科學平台的構建經驗。他的興趣位於機器學習和軟體工程的交集,並對商業領域有相當的理解。他是區域和全國 Python 社群的成員,也是 pySBD 的作者,這是一個用於句子分割的 NLP 開源 Python 庫,受到 ExplosionAI(spaCy)和 AllenAI(scispaCy)組織的認可。
**Mohan Kumar Silaparasetty** 是一位資深的深度學習和人工智慧專業人士。他畢業於印度理工學院卡哈爾古爾(IIT Kharagpur),擁有超過 25 年的行業經驗,擔任多種角色。在成功的企業職業生涯後,Mohan 開始了他的創業之旅,並成為 Trendwise Analytics 的共同創辦人和 CEO。這家公司提供人工智慧和深度學習的諮詢和培訓服務。他也是班加羅爾人工智慧聚會小組的組織者,該小組擁有超過 3500 名成員。
**Anthony So** 是一位出色的領導者,擁有超過 13 年的經驗。他因其分析能力和數據驅動的方法而受到認可,能夠解決複雜的商業問題並推動績效改進。他也是一位成功的教練和導師,擅長統計分析,並在使用 Python 進行機器學習方面具有專業知識。
目錄大綱
Table of Contents
- Building Blocks of Deep Learning
- Neural Networks
- Image Classification with Convolutional Neural Networks (CNNs)
- Deep Learning for Text - Embeddings
- Deep Learning for Sequences
- LSTMs, GRUs, and Advanced RNNs
- Generative Adversarial Networks
目錄大綱(中文翻譯)
Table of Contents
- Building Blocks of Deep Learning
- Neural Networks
- Image Classification with Convolutional Neural Networks (CNNs)
- Deep Learning for Text - Embeddings
- Deep Learning for Sequences
- LSTMs, GRUs, and Advanced RNNs
- Generative Adversarial Networks