May 11 2023

Learn TensorFlow in an Hour


Learn TensorFlow in  an Hour

Learn TensorFlow in an Hour
Published 5/2023
Created by Manish Shivanandhan
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + srt | Duration: 14 Lectures ( 48m ) | Size: 306 MB


Build a Handwriting Recognition deep neural network using Computer Vision


What you'll learn
Understand Tensors and Tensorflow
Learn how to generate Tensors
Learn basic operations using Tensorflow
Build a Handwriting recognition deep learning model using Tensorflow
Requirements
Basic knowledge of how machine learning works. Resources will be provided in the introduction.
Description
If you're interested in building and training machine learning models, TensorFlow is a powerful program that can help you do that. This course offers an introduction to TensorFlow and provides instruction on how to use it to build deep-learning AI models. One of the benefits of TensorFlow is its flexibility and ability to work with datasets of all sizes.Throughout the course, you'll learn about Tensors and Tensorflow in detail and discover how to work with them. Additionally, you'll gain a solid understanding of how to use TensorFlow to create models for different types of datasets. This includes working with GPUs and TPUs, which are specialized computer chips. These chips helps expand the capabilities of TensorFlow and improve its efficiency, particularly when working with large datasets.Finally, we will build a computer vision project where you'll have the opportunity to create a simple TensorFlow model that can recognize handwritten images. By the end of this course, you'll have a firm grasp of what TensorFlow is, how it works, and how to use it to develop machine learning models. So, if you're ready to dive into the world of deep learning and explore what TensorFlow has to offer, let's get started!
Who this course is for
Beginner python developers with basic understanding of machine learning looking to understand how to work with Tensorflow.

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