Deep Learning has caused the revival of Artificial Intelligence.
It has become the dominant method for speech recognition (Google
Assistant), computer vision (search for "my pictures" on Google
Photos), language translation, and even game-related Artificial
Intelligence (think AlphaGo and DeepMind). If you'd like to learn
how these systems work and maybe make your own, Deep Learning is
In this course, you’ll gain a solid understanding of Deep Learning models and use Deep Learning techniques to solve business and other real-world problems to make predictions quickly and easily. You’ll learn various Deep Learning approaches such as CNN, RNN, and LSTM and implement them with TensorFlow 2.0. You’ll program a model to classify breast cancer, predict stock market prices, process text as part of Natural Language Processing (NLP), and more.
By the end of this course, you’ll have a complete understanding to use the power of TensorFlow 2.0 to train Deep Learning models of varying complexities, without any hassle.
Table of Contents:
1 Deep Learning Introduction and Environment Setup
2 Building First Neural Network for Tabular Data with TensorFlow 2.0
3 Convolutional Neural Networks with TensorFlow 2.0
4 Recurrent Neural Network with TensorFlow 2.0
5 Long Short-Term Memory Networks (LSTM)
6 Transfer Learning with TensorFlow 2.0