TensorFlow Python
Comprehend the essential fundamentals of Machine Learning using TensorFlow Python through our free course. Learn neural networks, image classification, and tensor concepts online.
4.46
Intermediate
3.75 Hrs
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About this course
TensorFlow is an open-source library used for creating machine learning models. There are various uses of TensorFlow that particularly focuses on training and deploying deep neural networks. You will get familiar with deep learning, TensorFlow library, tensors, image classification, and neural network concepts of Machine Learning and Artificial Intelligence. Further, you will be learning how you can create deep learning models through the hands-on demonstration given by the tutor. Enroll in this free course and complete all the modules, followed by a quiz to gain a course completion certificate. Are you up for stepping into an advanced career in Machine Learning? Great Learning provides professional Artificial Intelligence and Machine Learning courses that cover all the important concepts to help you build a career in this domain. Enroll in the paid programs of Great Learning to advance your skills and achieve a certificate.
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Course Outline
Introduction for TensorFlow
With the high demand for Deep Learning, it is essential to learn about TensorFlow to create Deep Learning models. Here, we will learn what TensorFlow is, the essential library, and the in-demand skill.
What are Tensors?
This section will discuss the prerequisites to understand tensors, including Linear Algebra, Vector Calculus, and Python Calculus, and how they work together to provide effective results.
How to install TensorFlow?
In this section, you will learn about the latest version and compatibility and how you can install TensorFlow based on what GUI/CLI you use for Python.
Getting Started with TensorFlow
In this section, you will understand what a Tensor looks like, how it works, how we can programmatically write the Tensor, and how to get it to perform operations for us eventually.
Demo #1: MNIST Character Recognition with TensorFlow
This will be a hands-on session discussing 2 use cases: Digit classification using the MNIST dataset & image classification using CNN. This chapter will talk about the former demo.
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