Deep-Dive into Tensorflow Activation Functions

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Overview

You've learned how to use Tensorflow. You've learned the important functions, how to design and implement sequential and functional models, and have completed several test projects. What's next? It's time to take a deep dive into activation functions, the essential function of every node and layer of a neural network. These functions decide whether to fire or not to fire and add an element of non-linearity in most cases.

In this 2-hour course-based project, you will join me in an in-depth exploration of an exhaustive list of activation functions usable in Tensorflow and other frameworks. I will explain the working details of each activation function, describe the differences between each, and outline their pros and cons. Moreover, I will demonstrate each function being used, both from scratch and within Tensorflow.

Join me and boost your AI & machine learning knowledge while also earning a certificate to enhance your resume! Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.

Categories: Artificial Intelligence Courses, Machine Learning Courses, TensorFlow Courses, Programming Courses

Syllabus


Taught by

Charles Ivan Niswander II


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