Course Description

Full Stack Computer Vision Tutorial with Tensorflow, Python, Tensorflow.JS with React.JS If you are interested in learning how to develop a full-stack computer vision application, then this course is for you. In this comprehensive tutorial, you will learn how to create a computer vision application using some of the most popular tools in the industry, including Tensorflow, Python, Tensorflow.js, and React.js. The course starts by introducing you to the basics of computer vision and its various applications. You will learn how to identify objects in an image, recognize faces, and track objects in real-time. You will also learn how to use convolutional neural networks (CNNs) to perform image classification, object detection, and segmentation. Once you have a solid understanding of the fundamentals of computer vision, the course moves on to cover the practical aspects of developing a full-stack computer vision application. You will start by learning how to use Python and Tensorflow to train your models on large datasets. You will learn how to fine-tune pre-trained models and build your own custom models from scratch. Next, the course covers the deployment of your models to the web using Tensorflow.js. You will learn how to convert your trained models into a format that can be loaded into the browser and used in real-time. You will also learn how to integrate Tensorflow.js with React.js, one of the most popular frontend libraries for building modern web applications. The course concludes with a project where you will develop a full-stack computer vision application from scratch. You will learn how to build a user-friendly interface using React.js and integrate it with your Tensorflow.js models to perform real-time object detection. By the end of this course, you will have a solid understanding of how to develop a full-stack computer vision application using some of the most popular tools in the industry. You will be equipped with the skills and knowledge needed to build your own computer vision applications and take your career to the next level. Author: Nicholas Renotte