Neural Network from Scratch in TensorFlow

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In this Guided Project, you will:
2 hours
Intermediate
No download needed
Split-screen video
English
Desktop only

In this 2-hours long project-based course, you will learn how to implement a Neural Network model in TensorFlow using its core functionality (i.e. without the help of a high level API like Keras). You will also implement the gradient descent algorithm with the help of TensorFlow's automatic differentiation. While it’s easier to get started with TensorFlow with the Keras API, it’s still worth understanding how a slightly lower level implementation might work in tensorflow, and this project will give you a great starting point. In order to be successful in this project, you should be familiar with python programming, TensorFlow basics, conceptual understanding of Neural Networks and gradient descent. 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.

Skills you will develop

  • Data Science

  • Deep Learning

  • Mathematical Optimization

  • Artificial Neural Network

  • Tensorflow

Learn step-by-step

In a video that plays in a split-screen with your work area, your instructor will walk you through these steps:

How Guided Projects work

Your workspace is a cloud desktop right in your browser, no download required

In a split-screen video, your instructor guides you step-by-step

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