Dive into a comprehensive 14-hour course on deep learning, covering essential topics from image classification to generative adversarial networks. Learn to implement data cleaning techniques, build neural networks from scratch, and explore advanced concepts like regularization and convolutions. Master practical skills in natural language processing, tabular data analysis, and collaborative filtering while gaining insights into data ethics and the intricacies of back propagation and accelerated stochastic gradient descent.
Overview
Syllabus
Lesson 1: Deep Learning 2019 - Image classification.
Lesson 2: Deep Learning 2019 - Data cleaning and production; SGD from scratch.
Lesson 3: Deep Learning 2019 - Data blocks; Multi-label classification; Segmentation.
Lesson 4: Deep Learning 2019 - NLP; Tabular data; Collaborative filtering; Embeddings.
Lesson 5: Deep Learning 2019 - Back propagation; Accelerated SGD; Neural net from scratch.
Lesson 6: Deep Learning 2019 - Regularization; Convolutions; Data ethics.
Lesson 7: Deep Learning 2019 - Resnets from scratch; U-net; Generative (adversarial) networks.
Taught by
Jeremy Howard
