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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!

Created by Lazy Programmer Team, Lazy Programmer Inc. | 23 hours on-demand video course

This course is for beginner-level students all the way up to expert-level students. How can this be? If you’ve just taken my free Numpy prerequisite, then you know everything you need to jump right in. We will start with some very basic machine learning models and advance to state of the art concepts. Along the way, you will learn about all of the major deep learning architectures, such as Deep Neural Networks, Convolutional Neural Networks (image processing), and Recurrent Neural Networks (sequence data).

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
  • VIP Content: Build your own DeepDream Model
  • VIP Content: Build your own Object Localization Model

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Time Series Analysis, Forecasting, and Machine Learning in Python

Machine Learning: Natural Language Processing in Python (V2)

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PyTorch: Deep Learning and Artificial Intelligence

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