Deep Learning

Learn advanced state-of-the-art deep learning techniques and their applications using popular Python libraries

Leverage the power of deep learning and Keras to develop smarter and more efficient data models

Learn the essential background and model functioning of various neural network architectures such as CNN. RNN. LSTM, GANs, Autoencoders and more using best practices from an industry expert

Apply modern deep learning techniques to build and train deep neural networks using Gorgonia

Implement popular deep learning techniques to make your IoT applications smarter

Understand the core concepts of deep learning and deep reinforcement learning by applying them to develop games

Understand basic to advanced deep learning algorithms, the mathematical principles behind them, and their practical applications.

Introduction to deep learning and PyTorch by building a convolutional neural network and recurrent neural network for real-world use cases such as image classification, transfer learning, and natural language processing.

Build and train neural network models with high speed and flexibility in text, vision, and advanced analytics using PyTorch 1.x

Learn how to train popular deep learning architectures such as autoencoders, convolutional and recurrent neural networks while discovering how you can use deep learning models in your software applications with Microsoft Cognitive Toolkit

Build and train scalable neural network models on various platforms by leveraging the power of Caffe2

A comprehensive guide to advanced deep learning techniques, including Autoencoders, GANs, VAEs, and Deep Reinforcement Learning, that drive today's most impressive AI results