NPTEL - Indian Institute of Science, Bengaluru

Lec 46 Application to Materials Science
Lec 46 Application to Materials Science
Lec 45 Application to Materials Science
Lec 45 Application to Materials Science
Lec 44 Application to Materials Science
Lec 44 Application to Materials Science
Lec 43 Detection of electrons and ECCI
Lec 43 Detection of electrons and ECCI
Lec 42 Image Formation
Lec 42 Image Formation
Lec 41 Defect analysis
Lec 41 Defect analysis
Lec 40 Imaging
Lec 40 Imaging
Lec 39 Diffraction Patterns
Lec 39 Diffraction Patterns
Lec 38 Electron Diffraction
Lec 38 Electron Diffraction
Lec 37 TEM column cross-section
Lec 37 TEM column cross-section
Lec 36 Electron specimen interaction
Lec 36 Electron specimen interaction
Lec 65 Neural Networks with Tensorflow (Tutorial II)
Lec 65 Neural Networks with Tensorflow (Tutorial II)
Lec 64 Neural Networks with Tensorflow (Tutorial I)
Lec 64 Neural Networks with Tensorflow (Tutorial I)
Lec 63 Variational Autoencoders and Bayesian Generative Modeling
Lec 63 Variational Autoencoders and Bayesian Generative Modeling
Lec 62 Graph Neural Networks and Generative AI Fundamentals
Lec 62 Graph Neural Networks and Generative AI Fundamentals
Lec 61 Recurrent Neural Networks and Sequential Data Processing
Lec 61 Recurrent Neural Networks and Sequential Data Processing
Lec 60 Neural Network Challenges (Gradients, Overfitting) and Logic Gate Implementation
Lec 60 Neural Network Challenges (Gradients, Overfitting) and Logic Gate Implementation
Lec 59 Challenges in Training Neural Networks and their Mitigation
Lec 59 Challenges in Training Neural Networks and their Mitigation
Lec 58 Training an Artificial Neural Network:Forward Propagation,Backpropagation,and Hyperparameters
Lec 58 Training an Artificial Neural Network:Forward Propagation,Backpropagation,and Hyperparameters
Lec 57 Mathematical Foundation and Activation Functions of Neural Networks
Lec 57 Mathematical Foundation and Activation Functions of Neural Networks
Lec 56 Overview of Advanced Neural Network Architectures: From CNNs to GANs and GNNs
Lec 56 Overview of Advanced Neural Network Architectures: From CNNs to GANs and GNNs
Lec 46 Concluding the Asymptotic Analysis of Q-Learning
Lec 46 Concluding the Asymptotic Analysis of Q-Learning
Lec 45 Asymptotic Behaviour of the Q-Learning Limit ODE — A Switching Systems Perspective
Lec 45 Asymptotic Behaviour of the Q-Learning Limit ODE — A Switching Systems Perspective
Lec 44 Asymptotic Analysis of Q-Learning Algorithm
Lec 44 Asymptotic Analysis of Q-Learning Algorithm
Lec 43 Best Policy Algorithm for Q-Value Functions: A Stochastic Approximation Formulation
Lec 43 Best Policy Algorithm for Q-Value Functions: A Stochastic Approximation Formulation
Lec 57 Practical: Grid Loading & Imaging Software
Lec 57 Practical: Grid Loading & Imaging Software
Lec 56 Practical: Cryo-EM Grid Clipping
Lec 56 Practical: Cryo-EM Grid Clipping
Lec 55 Practical: Cryo-EM Plunge Freezing
Lec 55 Practical: Cryo-EM Plunge Freezing
Lec 54 Practical: TEM Setup & Negative Staining
Lec 54 Practical: TEM Setup & Negative Staining
Lec 70 Course Summary, Credits & Acknowledgments
Lec 70 Course Summary, Credits & Acknowledgments