Literacy Essentials: Core Concepts Recurrent Neural Networks
Literacy Essentials: Core Concepts Recurrent Neural Networks
.MP4, AVC, 1280x720, 30 fps | English, AAC, 2 Ch | 1h 9m | 154 MB
Instructor: Tapan Ghatalia
.MP4, AVC, 1280x720, 30 fps | English, AAC, 2 Ch | 1h 9m | 154 MB
Instructor: Tapan Ghatalia
This course will teach you how state of the art applications neural net applications such as time series, chat bots or language translation can be built with different types of Neural Networks using Python.
Organizations these days sits on massive piles of unstructured data, hence the data processing and advanced analytics applications also scales leaps and bounds. In this course, Literacy Essentials : Core Concepts Recurrent Neural Networks, you’ll learn to build state of the art RNN Applications. First, you’ll explore backpropagation in a neural network. Next, you’ll discover two different types of RNN such as LSTM and GRU. Finally, you’ll learn how to resolve a real time application with LSTM and GRU. When you’re finished with this course, you’ll have the skills and knowledge of Recurrent Neural Network needed to build state of the art AI applications.
Literacy Essentials: Core Concepts Recurrent Neural Networks
