Tensorflow 2.0: Deep Learning and Artificial Intelligence

Tensorflow 2.0: Deep Learning and Artificial Intelligence

Neural Networks for Computer Vision, Time Series Forecasting, NLP, GANs, Reinforcement Learning, and More!

What you’ll learn

  • Artificial Neural Networks (ANNs) / Deep Neural Networks (DNNs)
  • Predict Stock Returns
  • Time Series Forecasting
  • Computer Vision
  • How to build a Deep Reinforcement Learning Stock Trading Bot
  • GANs (Generative Adversarial Networks)
  • Recommender Systems
  • Image Recognition
  • Convolutional Neural Networks (CNNs)
  • Recurrent Neural Networks (RNNs)
  • Use Tensorflow Serving to serve your model using a RESTful API
  • Use Tensorflow Lite to export your model for mobile (Android, iOS) and embedded devices
  • Use Tensorflow’s Distribution Strategies to parallelize learning
  • Low-level Tensorflow, gradient tape, and how to build your own custom models
  • Natural Language Processing (NLP) with Deep Learning
  • Demonstrate Moore’s Law using Code
  • Transfer Learning to create state-of-the-art image classifiers

Requirements

  • Know how to code in Python and Numpy
  • For the theoretical parts (optional), understand derivatives and probability

Who this course is for:

  • Beginners to advanced students who want to learn about deep learning and AI in Tensorflow 2.0

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