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Deep-Dive into Tensorflow Activation Functions

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, deciding whether to fire or not to fire, and adding an element of non-linearity (in most cases). In this 2 hour course-based project, you will join me in a deep-dive into 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 their pros and cons, and I will demonstrate each function being used, both from scratch and within Tensorflow. Join me and boost your AI & machine learning knowledge, while also receiving a certificate to boost your resume in the process! 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.
Duration 7 Months
Institution Coursera
Format Online

Eligibility Criteria

school

Academic Foundation

A recognized Bachelor’s degree or high school equivalent required for admission into Coursera.

language

Language Proficiency

English proficiency required. IELTS, TOEFL, or standard medium-of-instruction certificates accepted.

Detailed Fees Breakdown

Base Tuition Fee $173
Total Est. Investment $173

Scholarships and early-bird waivers may apply. Contact admissions for exact institutional fees.

Academic Trajectory

Program Outcome

Graduates of the Deep-Dive into Tensorflow Activation Functions program at Coursera are equipped with global perspectives, ready to excel in international markets and top-tier career opportunities.

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