Deep Learning II - Joan Bruna NYU
Offered By: Paul G. Allen School via YouTube
Course Description
Overview
Explore advanced concepts in deep learning through this comprehensive lecture by Joan Bruna from NYU, covering topics such as symmetry, transformations, time series analysis, continuous domain applications, geometric stability, convolutional networks, and scattering representations. Delve into the intricacies of reproducing kernels, convolutional kernel networks, and spatial support while gaining insights into various deep learning models and their applications.
Syllabus
Introduction
Motivation
Symmetry
Transformations
Time Series
Continuous Domain
Geometric Stability
Convolutional Network
Other Models
Spatial Support
Convolutional Kernel Networks
Reproducing Kernels
Scattering Representation
Taught by
Paul G. Allen School
Related Courses
Business Analytics Using ForecastingNational Tsing Hua University via FutureLearn Introduction to Trading, Machine Learning & GCP
Google Cloud via Coursera Formação Cientista de Dados: O Curso Completo
Udemy 16+ Saat Python ile Veri Bilimi ve Makine Öğrenmesi
Udemy Configuring Prometheus to Collect Metrics
Pluralsight