This course teaches the key concepts of deep learning and how to implement them in a real-life project using PyTorch and Python. The learning outcomes include understanding RNNs, LSTMs, sequence modeling, and building a chatbot in PyTorch. The course requires basic high school mathematics, programming knowledge, and neural network understanding. The teaching method involves video tutorials covering various topics, including PyTorch introduction, tensors, and chatbot development. The course is intended for individuals interested in deep learning, specifically those looking to apply PyTorch in practical projects.
Overview
Syllabus
Recurrent Nerual Networks - RNNs and LSTMs.
Sequence-To-Sequence Models.
Attention Mechanisms.
Introduction to PyTorch.
PyTorch Tensors.
Chatbot: Processing the Dataset.
Chatbot: Data Preperation.
Chatbot: Building the Model.
Chatbot: Training the Model.
Taught by
freeCodeCamp.org
