What is TensorFlow.js and how is it used in web app development?

TensorFlow.js is a powerful library that allows developers to build and train machine learning models directly in the browser. This enables real-time inference on client devices, enhancing the user experience by reducing latency. By integrating TensorFlow.js into web apps, users can enjoy features like image recognition, natural language processing, and predictive text in a seamless manner. For instance, a web-based photo editing tool can use TensorFlow.js to analyze and automatically optimize user-uploaded images.

Who is the target audience for 'Practical TensorFlow.js: Deep Learning in Web App Development'?

The book primarily targets web developers, data scientists, and machine learning enthusiasts looking to harness deep learning techniques within their web applications. It is suitable for those with a basic understanding of JavaScript and web technologies who wish to delve into the practical applications of machine learning. For example, a developer who has experience in building web interfaces can utilize this resource to incorporate intelligent features into their applications, making them more robust and engaging.

What topics does 'Practical TensorFlow.js' cover?

'Practical TensorFlow.js' encompasses a wide range of topics including the fundamentals of machine learning, neural networks, and practical model-building techniques specifically in a web context. The book provides detailed examples and code snippets that illustrate how to implement various machine learning models seamlessly in web applications. Readers can expect to learn about personalized recommendations, sentiment analysis, and even training models directly in the browser, making it a comprehensive resource for aspiring machine learning developers.

Is prior knowledge of machine learning required to understand the content?

While some familiarity with machine learning concepts can be beneficial, the book is designed to cater to both beginners and those with experience in the field. It starts with a basic introduction to key concepts before moving into more complex topics related to TensorFlow.js. Practical exercises guide readers through real-world applications. For instance, a developer with no machine learning background can still grasp the implementation of image classification from scratch using the guided hands-on projects provided in the book.

Can I run TensorFlow.js models in offline mode?

Yes, TensorFlow.js supports running models offline in the browser. Once a model is trained or loaded, it can be executed without an internet connection, making it highly versatile for various applications. This is particularly advantageous for web apps that require quick responses, such as games or interactive tools, ensuring that users can enjoy seamless experiences even in low-connectivity environments. Offline models can also enhance privacy as user data can stay on their device.

What makes TensorFlow.js different from other machine learning libraries?

TensorFlow.js differentiates itself by enabling machine learning directly in the browser, allowing users to harness the processing power of their devices without server-side dependencies. This means that applications can run much faster and provide immediate feedback. It is perfect for use in scenarios like chatbots or interactive tutorials, where responsiveness enhances user engagement. Additionally, it supports training models on real users' data directly in the client environment, preserving privacy.

Are there any prerequisites for using 'Practical TensorFlow.js' effectively?

To effectively utilize 'Practical TensorFlow.js', readers should have a basic understanding of JavaScript as it is the primary programming language used throughout the book. Familiarity with web development concepts, including HTML and CSS, can also enhance the learning experience. Practical guided exercises, such as creating a machine learning-powered app, help bridge the gap for those new to the subject. A developer comfortable with JavaScript can quickly adapt to machine learning principles presented in the book.

How does 'Practical TensorFlow.js' facilitate hands-on learning?

'Practical TensorFlow.js' includes numerous hands-on projects and exercises, encouraging readers to actively engage with the material. Each chapter builds on previous knowledge, guiding readers through creating and training machine learning models. For instance, users can create a web app that predicts user preferences based on past behavior, using real-time data and feedback. This practical approach helps solidify understanding and encourages experimentation, a key element in mastering new technologies.

Can TensorFlow.js be integrated with other JavaScript frameworks?

Absolutely! TensorFlow.js can be integrated with popular JavaScript frameworks like React, Angular, and Vue.js. This flexibility allows developers to create highly interactive and dynamic applications that leverage machine learning. For instance, a React-based application could use TensorFlow.js to provide personalized recommendations based on user interactions, enhancing the overall user experience. This cross-compatibility makes it easier for developers to include machine learning capabilities in their existing projects.

如何從 Ubuy 在線購物 Practical TensorFlow.js: Deep Learning in Web App？

從 Ubuy 在線購物 Practical TensorFlow.js: Deep Learning in Web App 非常簡單。. 您只需搜索產品，在結賬時選擇運輸方式，然後將其運送到您所在的位置。

Practical TensorFlow.js: Deep Learning in Web App 可以在 Hong Kong 在線購物嗎？

是的，您可以在 Ubuy Hong Kong 以合理的價格購買該產品。. Practical TensorFlow.js: Deep Learning in Web App 在本地不可用，但您可以信任我們的快遞服務。

下訂單後需要多長時間才能收到產品？

您訂購的產品的交貨時間根據您訂購的商品和您選擇的運輸方式而有所不同。. 結賬時會提到預計送貨時間，所以購物時請放心。

觀看原文

Practical TensorFlow.js: Deep Learning in Web App Development

Develop and deploy deep learning web apps using the TensorFlow.js library.

物品 #: 127931870

Practical TensorFlow.js: Deep Learning in Web App Development

Q: Where can I buy Practical TensorFlow.js: Deep Learning in Web App Development 1st ed. Edition in Hong Kong?

You can purchase 'Practical TensorFlow.js: Deep Learning in Web App Development 1st ed. Edition' on Ubuy. They offer a comprehensive selection of books and products, ensuring a convenient shopping experience. With their user-friendly platform, you can easily find the book and have it delivered directly to your location. Ubuy is a reliable choice for obtaining educational resources like this to enhance your knowledge in web app development and machine learning.

88% of respondents would recommend this to a friend

物品 #: 127931870

HKD 545

~~HKD 724~~

Price Details

Excluding Shipping & Custom charges ( Shipping and custom charges will be calculated on checkout )

^{*All items will import from 美國}

您省下 : 25%

供應情形 : 有存貨

從USA商店導入

QTY:

現在訂購，約可在下列時間收貨：星期六, 十月 24

Secured transaction

Our Top Logistics Partners

Develop and deploy deep learning web apps using the TensorFlow.js library.

Paperback

U-Care Warranty:

None

選擇一個計劃

Fast
Shipping

Free
Return^*

Secure Packaging

100% Original Products

PCI DSS Compliance

ISO 27001 Certified

Note: Step Down Voltage Transformer required for using electronics products of 美國 store (110-120). Recommended power converters 立即購買.

What Stands Out

Hands-on Approach

This book emphasizes practical coding examples and hands-on projects, enabling readers to apply TensorFlow.js concepts directly in web app development, ensuring an engaging learning experience.

Web-Optimized Learning

Targeting web developers, it integrates deep learning techniques tailored for browser environments, making advanced machine learning accessible and relevant for frontend applications and enhancing user interactivity.

Comprehensive Resource

Combining theory and practice, it serves as a complete guide, from foundational knowledge to advanced applications, ensuring readers gain a robust understanding of deep learning in web contexts.

產品詳情

Develop and deploy deep learning web apps using the TensorFlow.js library. TensorFlow.js is part of a bigger framework named TensorFlow, which has many tools that supplement it, such as TensorBoard, ml5js, tfjs-vis. This book will cover all these technologies and show they integrate with TensorFlow.js to create intelligent web apps.The most common and accessible platform users interact with everyday is their web browser, making it an ideal environment to deploy AI systems. TensorFlow.js is a well-known and battle-tested library for creating browser solutions. Working in JavaScript, the so-called language of the web, directly on a browser, you can develop and serve deep learning applications.You'll work with deep learning algorithms such as feedforward neural networks, convolutional neural networks (CNN), recurrent neural networks (RNN), and generative adversarial network (GAN). Through hands-on examples, apply these networks in use cases related to image classification, natural language processing, object detection, dimensionality reduction, image translation, transfer learning, and time series analysis.Also, these topics are very varied in terms of the kind of data they use, their output, and the training phase. Not everything in machine learning is deep networks, there is also what some call shallow or traditional machine learning. While TensorFlow.js is not the most common place to implement these, you'll be introduce them and review the basics of machine learning through TensorFlow.js.What You'll LearnBuild deep learning products suitable for web browsersWork with deep learning algorithms such as feedforward neural networks, convolutional neural networks (CNN), recurrent neural networks (RNN), and generative adversarial network (GAN)Develop apps using image classification, natural language processing, object detection, dimensionality reduction, image translation, transfer learning, and time series analysisWho This Book Is For Programmers developing deep learning solutions for the web and those who want to learn TensorFlow.js with at least minimal programming and software development knowledge. No prior JavaScript knowledge is required, but familiarity with it is helpful.

Publisher	Apress
Publication date	September 19, 2020
Edition	First Edition
Language	English
Print length	327 pages
ISBN-10	1484262727
ISBN-13	978-1484262726
Item Weight	2.31 pounds (1.05 kg)
Dimensions	6.1 x 0.74 x 9.25 inches (15.5 x 1.9 x 23.5 cm)

Who Should Buy?

Web Developers
Ideal for developers wanting to integrate machine learning capabilities directly into their web applications using TensorFlow.js.
Data Science Students
A great resource for students learning to apply deep learning techniques within web technologies and JavaScript.
AI Enthusiasts
Perfect for individuals interested in exploring artificial intelligence and deep learning in a practical web development context.

Beginner Programmers
Not suitable for complete beginners who lack foundational knowledge of programming or JavaScript concepts.

產品敘述

有疑問？與我們聊天

客戶問題與解答

題: 如何從 Ubuy 在線購物 Practical TensorFlow.js: Deep Learning in Web App？

回答: 從 Ubuy 在線購物 Practical TensorFlow.js: Deep Learning in Web App 非常簡單。. 您只需搜索產品，在結賬時選擇運輸方式，然後將其運送到您所在的位置。
題: Practical TensorFlow.js: Deep Learning in Web App 可以在 Hong Kong 在線購物嗎？

回答: 是的，您可以在 Ubuy Hong Kong 以合理的價格購買該產品。. Practical TensorFlow.js: Deep Learning in Web App 在本地不可用，但您可以信任我們的快遞服務。
題: 下訂單後需要多長時間才能收到產品？

回答: 您訂購的產品的交貨時間根據您訂購的商品和您選擇的運輸方式而有所不同。. 結賬時會提到預計送貨時間，所以購物時請放心。

Intelligence & Semantics Editorial Review

未找到編輯評論

Customer Reviews & Ratings

4.1

7 客戶評分

5 星

63%
4 星

19%
3 星

0%
2 星

0%
1 星

18%

評價此產品

與其他客戶分享您的想法

優點

User-friendly for beginners
Comprehensive tutorials available
Great for web app integration
Strong community support
Covers latest deep learning trends

缺點

Some examples may require adjustments.

Product Price History

重要資訊

限制：如跨國購買產品，請注意製造商的保固有可能無效；製造商服務選項可能無法使用；產品手冊、教學、以及安全警示可能不會是目的地國家的語言；產品（與附加材料）設計也許不會符合目的地國家的標準、規格、以及標示要求；且產品也許不會符合目的地國家的伏特數值與其他電力標準（需要使用合適的變壓器或轉接器）。收件者須負責確定該產品在目的地國家可合法進口。當在 Ubuy 或其聯盟夥伴網站上訂購時，收件者為記錄上的進口者，且必須遵從目的地國家的法律與規範。
由於 Ubuy 是一個全球搜尋引擎，並不是所有列於 Ubuy 的產品都有出售。產品須受出口／貿易法規規範。

HKD 545

~~HKD 724~~

現在訂購，約可在下列時間收貨：星期六, 十月 24

QTY:

Secured transaction

PCI DSS compliant and ISO 27001:2022 certified, with encrypted payments and full buyer protection on every order.

Our Top Logistics Partners

Fastest cross-border delivery

特色和優勢

Learn to create intelligent web applications with TensorFlow.js.
Master deep learning algorithms like CNN, RNN, and GAN.
Utilize diverse applications such as image classification and natural language processing.
Integrate multiple tools like TensorBoard and ml5js with TensorFlow.js.
Build browser-friendly deep learning products from scratch.
Stay ahead in AI development with practical, hands-on examples.

Ubuy Assurance

Experience worry-free shopping with 100% original products, PCI DSS-compliant payment security, ISO 27001-certified data protection, the fastest cross-border delivery, free returns ^*, and secure packaging on every order.

Practical TensorFlow.js: Deep Learning in Web App Development