G
Grroups
Home
Marketplace
Refer & Earn
Premium Services
Jobs
Members Login
Toggle navigation
G
Grroups
Home
Jobs
Companies
Universities
Courses
Blogs
About Us
Contact Us
Login/Register
Deep Learning Demystified
Institute for Pure and Applied Mathematics
Duration  70 Hours (66 Videos)
Courseware
About the Course
Syllabus
Resourses / Notes
Online Classroom
Source
Donate
Deep Learning Demystified
Institute for Pure and Applied Mathematics
Duration  70 Hours (66 Videos)
Courseware
About the Course
Syllabus
Resourses
Online Classroom
Source
Donate
Course Index
Geoffrey Hinton: "Introduction to Deep Learning & Deep Belief Nets"
by Institute for Pure and Applied Mathematics
Geoffrey Hinton: "Using Backpropagation for FineTuning a Generative Model..."
by Institute for Pure and Applied Mathematics
Yann LeCun: "Deep Learning, Graphical Models, EnergyBased Models, Structured Prediction, Pt. 1"
by Institute for Pure and Applied Mathematics
Yann LeCun: "Deep Learning, Graphical Models, EnergyBased Models, Structured Prediction, Pt. 2"
by Institute for Pure and Applied Mathematics
Andrew Ng: "Deep Learning, SelfTaught Learning and Unsupervised Feature Learning"
by Institute for Pure and Applied Mathematics
Andrew Ng: "Advanced Topics + Research Philosophy / Neural Networks: Representation"
by Institute for Pure and Applied Mathematics
Andrew Ng: "Nonlinear Hypotheses, Pt. 1"
by Institute for Pure and Applied Mathematics
Andrew Ng: "Nonlinear Hypotheses, Pt. 2"
by Institute for Pure and Applied Mathematics
Yann LeCun: "Deep Learning, Graphical Models, EnergyBased Models, Structured Prediction, Pt. 3"
by Institute for Pure and Applied Mathematics
Geoffrey Hinton: "Some Applications of Deep Learning"
by Institute for Pure and Applied Mathematics
Geoffrey Hinton: "A Computational Principle that Explains Sex, the Brain, and Sparse Coding"
by Institute for Pure and Applied Mathematics
Rob Fergus: "Deep Learning Methods for Vision, Pt. 1"
by Institute for Pure and Applied Mathematics
Rob Fergus: "Deep Learning Methods for Vision, Pt. 2"
by Institute for Pure and Applied Mathematics
Geoffrey Hinton: "Does the Brain do Inverse Graphics?"
by Institute for Pure and Applied Mathematics
Alan Yuille: "Compositional Models"
by Institute for Pure and Applied Mathematics
Graham Taylor: "Learning Representations of Sequences"
by Institute for Pure and Applied Mathematics
Graham Taylor: "Feature Learning for Comparing Examples"
by Institute for Pure and Applied Mathematics
Alan Yuille: "Unsupervised Compositional Learning of Object Models"
by Institute for Pure and Applied Mathematics
Alan Yuille: "Learning Discriminative Models of Objects and Images"
by Institute for Pure and Applied Mathematics
Yann LeCun: "Deep Learning, Graphical Models, EnergyBased Models, Structured Prediction, Pt. 4"
by Institute for Pure and Applied Mathematics
Yoshua Bengio: "Representation Learning and Deep Learning, Pt. 1"
by Institute for Pure and Applied Mathematics
Yoshua Bengio: "Representation Learning and Deep Learning, Pt. 2"
by Institute for Pure and Applied Mathematics
Stephen Wright: " Some Relevant Topics in Optimization, Pt. 1"
by Institute for Pure and Applied Mathematics
Arthur Szlam: "A Tutorial on Sparse Modeling"
by Institute for Pure and Applied Mathematics
Stephen Wright: "Some Relevant Topics in Optimization, Pt. 2"
by Institute for Pure and Applied Mathematics
Stephen Wright: "Sparse and Regularized Optimization, Pt. 1"
by Institute for Pure and Applied Mathematics
Stephen Wright: "Sparse and Regularized Optimization, Pt. 2"
by Institute for Pure and Applied Mathematics
Arthur Szlam: "Accelerating Sparse Coding Via Learning"
by Institute for Pure and Applied Mathematics
Yoshua Bengio: "Representation Learning and Deep Learning, Pt. 4"
by Institute for Pure and Applied Mathematics
Yoshua Bengio: "Representation Learning and Deep Learning, Pt. 3"
by Institute for Pure and Applied Mathematics
Stéphane Mallat: "Scattering Invariant Deep Networks for Classification, Pt. 1"
by Institute for Pure and Applied Mathematics
Stéphane Mallat: "Scattering Invariant Deep Networks for Classification, Pt. 2"
by Institute for Pure and Applied Mathematics
Kai Yu: "Image Classification Using Sparse Coding, Pt. 1"
by Institute for Pure and Applied Mathematics
Kai Yu: "Image Classification Using Sparse Coding, Pt. 2"
by Institute for Pure and Applied Mathematics
Jorge Nocedal: "Tutorial on Optimization Methods for Machine Learning, Pt. 1"
by Institute for Pure and Applied Mathematics
Jorge Nocedal: "Tutorial on Optimization Methods for Machine Learning, Pt. 2"
by Institute for Pure and Applied Mathematics
Jorge Nocedal: "Tutorial on Optimization Methods for Machine Learning, Pt. 3"
by Institute for Pure and Applied Mathematics
Stéphane Mallat: "Scattering Invariant Deep Networks for Classification, Pt. 3"
by Institute for Pure and Applied Mathematics
Jason Morton: "An Algebraic Perspective on Deep Learning, Pt. 1"
by Institute for Pure and Applied Mathematics
Jason Morton: "An Algebraic Perspective on Deep Learning, Pt. 2"
by Institute for Pure and Applied Mathematics
Jason Morton: "An Algebraic Perspective on Deep Learning, Pt. 3"
by Institute for Pure and Applied Mathematics
Yoshua Bengio: "Representation Learning and Deep Learning, Pt. 5"
by Institute for Pure and Applied Mathematics
Stanley Osher: "Compressed Sensing: Recovery, Algorithms, and Analysis"
by Institute for Pure and Applied Mathematics
Stanley Osher: "Linearized Bregman Algorithm for L1regularized Logistic Regression"
by Institute for Pure and Applied Mathematics
Ruslan Salakhutdinov: "Learning Hierarchical Generative Models, Pt. 1"
by Institute for Pure and Applied Mathematics
Ruslan Salakhutdinov: "Learning Hierarchical Generative Models, Pt. 2"
by Institute for Pure and Applied Mathematics
Marc'Aurelio Ranzato: "Deep Gated MRFs, Pt. 1"
by Institute for Pure and Applied Mathematics
Marc'Aurelio Ranzato: "Deep Gated MRFs, Pt. 2"
by Institute for Pure and Applied Mathematics
Jason Weston: "Large Scale Supervised Embedding for Text and Images"
by Institute for Pure and Applied Mathematics
Jason Weston: "Deep Learning for Natural Language Processing"
by Institute for Pure and Applied Mathematics
Jason Weston: "Situated Learning: Hidden Representations for Grounding Language"
by Institute for Pure and Applied Mathematics
Ruslan Salakhutdinov: "Advanced Hierarchical Models"
by Institute for Pure and Applied Mathematics
Bruno Olshausen: "From Natural Scene Statistics to Models of Neural Coding & Representation, Pt. 1"
by Institute for Pure and Applied Mathematics
Marc'Aurelio Ranzato: "Large Scale Deep Learning"
by Institute for Pure and Applied Mathematics
Thomas Serre: "Deep Learning in the Visual Cortex, Pt. 1"
by Institute for Pure and Applied Mathematics
Thomas Serre: "Deep Learning in the Visual Cortex, Pt. 2"
by Institute for Pure and Applied Mathematics
Roland Memisevic: "Multiview Feature Learning, Pt. 1"
by Institute for Pure and Applied Mathematics
Roland Memisevic: "Multiview Feature Learning, Pt. 2"
by Institute for Pure and Applied Mathematics
Bruno Olshausen: "From Natural Scene Statistics to Models of Neural Coding & Representation, Pt. 2"
by Institute for Pure and Applied Mathematics
Iain Murray: "Introduction to MCMC for Deep Learning"
by Institute for Pure and Applied Mathematics
Iain Murray: "Density Estimation"
by Institute for Pure and Applied Mathematics
Nando de Freitas: "An Informal Mathematical Tour of Feature Learning, Pt. 1"
by Institute for Pure and Applied Mathematics
Nando de Freitas: "An Informal Mathematical Tour of Feature Learning, Pt. 2"
by Institute for Pure and Applied Mathematics
Thomas Serre: "Deep Learning in the Visual Cortex, Pt. 3"
by Institute for Pure and Applied Mathematics
Nando de Freitas: "An Informal Mathematical Tour of Feature Learning, Pt. 3"
by Institute for Pure and Applied Mathematics
Nando de Freitas: "An Informal Mathematical Tour of Feature Learning, Pt. 4"
by Institute for Pure and Applied Mathematics
Comments
Leave a Comment
Post a Comment
Built By
Name
Institute for Pure and Applied Mathematics
Total Courses
1
Share this courses now
Classroom (304)
Prakash Verma
Isaac Siu
Harsh Wardhan
Clifford Reynolds
Tushar Chauhan
Mukul Virmani
David Bethge
Zhibing Liu
Saket Tiwari
View all
Built By
Name
Institute for Pure and Applied Mathematics
Total Courses
1
Share this courses now
Classroom (304)
Prakash Verma
Isaac Siu
Harsh Wardhan
Clifford Reynolds
Tushar Chauhan
Mukul Virmani
David Bethge
Zhibing Liu
Saket Tiwari
View all
Already a member ?
Login
Remember me

Forgot password?
Gladwin Analytics
International Big Data Analytics Media
(or)
Male
Female
By Clicking Sign up, you agree to our
Terms of Use
,
Privacy Policy and Data Policy
.
Sign Up
Leave a Comment