Artificial Intelligence

Start Learning Tensorflow JS today!

Join Turtlers Coding lessons today to enjoy flexible class appointments and teaching methods that allows you/your kids to explore their creative outlook and use modern technology to implement applicable projects. Start today to get right on your learning path.

Intermediate
Last updated 9/2023
English

Course Description

Do you want to learn how to use TensorFlow.js, the JavaScript library for machine learning, in your web applications? If so, this course is for you! In this course, we start with module one which covers how to install and run TensorFlow.js on different platforms, such as browsers, servers, and mobile devices. We move on to how to use tensors, the basic data structures of TensorFlow.js, to store and manipulate multidimensional data. Module two, delves into creating and using machine learning models with TensorFlow.js, such as classifiers, object detectors, and recommendation systems.

Module three covers how to use advanced features of TensorFlow.js, such as image processing, user interface, model conversion, and data analysis. Module four covers how to train your own models with TensorFlow.js, using both synthetic and real-world data sets.

By the end of this course, you will have a solid understanding of the concepts and techniques of TensorFlow.js, and you will be able to build your own web applications with machine learning capabilities. You will also have access to various resources and tools that will help you further your learning and development with TensorFlow.js. This course is suitable for beginners who have some basic knowledge of JavaScript and web development. No prior experience with machine learning or TensorFlow is required. Enroll now and start your journey with TensorFlow.js!

A Laptop (Windows, Mac or Linux are all acceptable)
React Development 2 (JS & Node)

Upon completion of the course, the student is should comfortably be able to:

Set up and use TensorFlow.js on different platforms, such as client and server environments, and apply it to run a sentiment classifier on text data.
Gain an understanding of tensors and use this knowledge to create a basic recommendation system for music, demonstrating your ability to work with fundamental data structures in machine learning.
Explore the manipulation of image data, uncovering techniques for modifying and analyzing complex image data sets.
Develop the skills to implement various machine learning models, gaining insights into the core principles that drive machine learning applications.
Create machine learning models for object detection, build visual overlays to display results, and connect the models to webcams for real-time inference.