Deep Learning Course Content
Introduction to Machine Learning
The domain of machine learning and its implications to the artificial intelligence sector, the advantages of machine learning over other conventional methodologies.
Deep Learning Techniques
Introduction to Deep Learning within machine learning, how it differs from all others methods of machine learning, training the system with training data, supervised and unsupervised learning, classification and regression supervised learning, clustering and association unsupervised learning, the algorithms used in these types of learning.
TensorFlow for Training Deep Learning Model
Introduction to TensorFlowopen source software library for designing, building and training Deep Learning models, Python Library behind TensorFlow, Tensor Processing Unit (TPU) programmable AI accelerator by Google.
Introduction to Neural Networks
Mapping the human mind with Deep Neural Networks, the various building block of Artificial Neural Networks, the architecture of DNN, its building blocks, the concept of reinforcement learning in DNN, the various parameters, layers, activation functions and optimization algorithms in DNN.
Using GPUs to train Deep Learning networks
Introduction to GPUs and how they differ from CPUs, the importance of GPUs in training Deep Learning Networks, the forward pass and backward pass training technique, the GPU constituent with simpler core and concurrent hardware.