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TensorFlow for Deep Learning with Python

TensorFlow for Deep Learning with Python
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58 Learners

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26 Videos

Video Course

Course Overview

The “TensorFlow for Deep Learning with Python” course is designed to help you gain knowledge of Deep Learning models using TensorFlow. You will learn the architectures of common deep learning models, implement them in TensorFlow  2.0 and learn to optimize them.

Prerequisites

Anyone interested in this program needs to have:

    • Basic knowledge of Python, math
    • Suggested: Basic understanding of AI, ML

 

Key Takeaways

      • Basics of Deep Learning
      • Learn how to build in TensorFlow 2.0:
        • Multilayer Perceptron
        • Convolutional Neural Network
        • Recurrent Neural Network
        • Generative adversarial network
        • Auto Encoder
        • Variational Autoencoder
      • Re-enforcement Learning
      • Metrics, model tuning, loss functions
      • TensorFlow Lite

 

Target Audience:

    • Mathematicians, computer scientists
    • Anyone interested in AI, ML and TenorFlow 2.0

Included in this course

  • cloud.svgvideo.svg
    Video Course26 Videos Available
Introduction
 lecture
  • video.svgIntroduction to deep learning
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    17m 20s
Topic-wise Content Distribution
Introduction
  • video.svgIntroduction to deep learning
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    17m 20s

Frequently Asked Questions