Key Features
- Build microservices to perform data transformation and ML model serving in JavaScript
- Explore what Danfo.js is and how it helps with data analysis and data visualization
- Combine Danfo.js and TensorFlow.js for machine learning
Book Description
Most data analysts use Python and pandas for data processing for the convenience and performance these libraries provide. However, JavaScript developers have always wanted to use machine learning in the browser as well. This book focuses on how Danfo.js brings data processing, analysis, and ML tools to JavaScript developers and how to make the most of this library to build data-driven applications.
Starting with an overview of modern JavaScript, you'll cover data analysis and transformation with Danfo.js and Dnotebook. The book then shows you how to load different datasets, combine and analyze them by performing operations such as handling missing values and string manipulations. You'll also get to grips with data plotting, visualization, aggregation, and group operations by combining Danfo.js with Plotly. As you advance, you'll create a no-code data analysis and handling system and create-react-app, react-table, react-chart, Draggable.js, and tailwindcss, and understand how to use TensorFlow.js and Danfo.js to build a recommendation system. Finally, you'll build a Twitter analytics dashboard powered by Danfo.js, Next.js, node-nlp, and Twit.js.
By the end of this app development book, you'll be able to build and embed data analytics, visualization, and ML capabilities into any JavaScript app in server-side Node.js or the browser.
What you will learn
- Perform data experimentation and analysis with Danfo.js and Dnotebook
- Build machine learning applications using Danfo.js integrated with TensorFlow.js
- Connect Danfo.js with popular database applications to aid data analysis
- Create a no-code data analysis and handling system using internal libraries
- Develop a recommendation system with Danfo.js and TensorFlow.js
- Build a Twitter analytics dashboard for sentiment analysis and other types of data insights
Who this book is for
This book is for data analysts, data scientists, and JavaScript developers who want to create data-driven applications in the JavaScript/Node.js environment. Intermediate-level knowledge of JavaScript programming and data science using pandas is expected.