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In this course, you will learn :
- Artificial Neural Networks.
- Multi-Layer Perceptions.
- Tensorflow.
- Keras.
- Convolutional Neural Networks.
- Recurrent Neural Networks.
Syllabus :
- The History of Artificial Neural Networks
- Hands-On in the Tensorflow Playground
- Deep Learning Details
- Introducing Tensorflow
- Using Tensorflow for Handwriting Recognition
- Introducing Keras
- Using Keras to Learn Political Affiliations
- Convolutional Neural Networks
- Using CNN's for Handwriting Recognition
- Recurrent Neural Networks
- Using RNN's for Sentiment Analysis
- Transfer Learning
- Tuning Neural Networks: Learning Rate and Batch Size Hyperparameters
- Deep Learning Regularization with Dropout and Early Stopping
- The Ethics of Deep Learning
- Variational Auto-Encoders (VAE's)
- VAE's: Hands-On with Fashion MNIST
- Generative Adversarial Networks (GAN's)
- GAN Demos & Live Training
- GAN's: Hands-On with Fashion MNIST
- Deep Learning Project Intro
- Deep Learning Project Solution
