Канал: Deep learning for all at IIT Mandi - Aditya Nigam

Evening Session1 July18

Evening Session1 July18

Morning Session July18

Morning Session July18

Evening Session_11_July

Evening Session_11_July

Morning Session2_11_July

Morning Session2_11_July

Morning Session1_11_July

Morning Session1_11_July

Evening Session_10_July

Evening Session_10_July

Morning Session_2_10_July

Morning Session_2_10_July

Morning Session1_10_July

Morning Session1_10_July

Evening Session_4_July

Evening Session_4_July

3. Deep Learning Intuition

3. Deep Learning Intuition

2. (Part B) Preliminary Deep Learning Lecture

2. (Part B) Preliminary Deep Learning Lecture

1. (Part A) Preliminary Deep Learning Lecture

1. (Part A) Preliminary Deep Learning Lecture

Loss_Function(Part-D)

Loss_Function(Part-D)

Loss_Function(Part C)

Loss_Function(Part C)

Loss Function(Part B)

Loss Function(Part B)

Loss_Function(Part A)

Loss_Function(Part A)

Graph1

Graph1

Graph2

Graph2

Graph3

Graph3

Graph4

Graph4

Python code(Pytorch) for Classification task without using predefined packages and modules

Python code(Pytorch) for Classification task without using predefined packages and modules

Policy evaluation, Policy improvement,

Policy evaluation, Policy improvement,

Overview of Deep Learning concepts

Overview of Deep Learning concepts

Introduction to Reinforcement Learning

Introduction to Reinforcement Learning

Reinforcement Learning framework

Reinforcement Learning framework

Optimal policy, Value function, Q-value function,

Optimal policy, Value function, Q-value function,

Deep Q Network

Deep Q Network

DQN Algorithm

DQN Algorithm

Introduction to Policy Gradient

Introduction to Policy Gradient

REINFORCE Algorithm

REINFORCE Algorithm

Revision from starting to DQN

Revision from starting to DQN

Graph Convolutional Neural Network - Part B

Graph Convolutional Neural Network - Part B

Graph Convolutional Neural Network - Part A

Graph Convolutional Neural Network - Part A

Transformer Series: Part-14 Transformer The Complete Architecture (Dr Aditya Nigam)

Transformer Series: Part-14 Transformer The Complete Architecture (Dr Aditya Nigam)

Transformer Series: Part-13 Transformer Decoder, Masked MHA (Dr Aditya Nigam)

Transformer Series: Part-13 Transformer Decoder, Masked MHA (Dr Aditya Nigam)

Transformer Series: Part-12 Positional Embedding (Dr Aditya Nigam)

Transformer Series: Part-12 Positional Embedding (Dr Aditya Nigam)

Transformer Series: Part-11 MHA, FF, Add and Norm Layer (Dr Aditya Nigam)

Transformer Series: Part-11 MHA, FF, Add and Norm Layer (Dr Aditya Nigam)

Transformer Series: Part-10 Self Attention Analogy (Dr Aditya Nigam)

Transformer Series: Part-10 Self Attention Analogy (Dr Aditya Nigam)

Transformer Series: Part-9 Calculating Self Attention (Dr Aditya Nigam)

Transformer Series: Part-9 Calculating Self Attention (Dr Aditya Nigam)

Transformer Series: Part-8 Query, Key, Value Matrices (Dr Aditya Nigam)

Transformer Series: Part-8 Query, Key, Value Matrices (Dr Aditya Nigam)

Transformer Series: Part-7 Query, Key, Value (Dr Aditya Nigam)

Transformer Series: Part-7 Query, Key, Value (Dr Aditya Nigam)

Transformer Series: Part-6 Cross Attention (Dr Aditya Nigam)

Transformer Series: Part-6 Cross Attention (Dr Aditya Nigam)

Transformer Series: Part-5 Self-Attention(Dr Aditya Nigam)

Transformer Series: Part-5 Self-Attention(Dr Aditya Nigam)

Transformer Series: Part-4 Transformer Encoder (Dr Aditya Nigam)

Transformer Series: Part-4 Transformer Encoder (Dr Aditya Nigam)

Transformer Series: Part-3 Batch Normalization and Layer Normalization (Dr Aditya Nigam)

Transformer Series: Part-3 Batch Normalization and Layer Normalization (Dr Aditya Nigam)

Transformer Series: Part-2 Problems with RNNs (Dr Aditya Nigam)

Transformer Series: Part-2 Problems with RNNs (Dr Aditya Nigam)

Transformer Series: Part-1 Basic Introduction (Dr. Aditya Nigam)

Transformer Series: Part-1 Basic Introduction (Dr. Aditya Nigam)

Lecture 4: Deep Q-Learning with Experience Replay

Lecture 4: Deep Q-Learning with Experience Replay

Lecture 3: Policy Evaluation, Value Iteration, Policy Iteration, Policy Improvement (with example)

Lecture 3: Policy Evaluation, Value Iteration, Policy Iteration, Policy Improvement (with example)

Lecture 2: Optimal Policy (pi*), Optimal Value and Q-Fn

Lecture 2: Optimal Policy (pi*), Optimal Value and Q-Fn

Lecture 1: Mathematical Formulation of RL using MDP

Lecture 1: Mathematical Formulation of RL using MDP

[Slow Soulful] Yiruma: River flowing in you (Limited Edition)

[Slow Soulful] Yiruma: River flowing in you (Limited Edition)

CS671_Online Lecture-7 (PART-E): (PosEmb) Transformer Networks

CS671_Online Lecture-7 (PART-E): (PosEmb) Transformer Networks

CS671_Online Lecture-7 (PART-D): Transformer Networks

CS671_Online Lecture-7 (PART-D): Transformer Networks

CS671_Online Lecture-7 (PART-C): Transformer Networks

CS671_Online Lecture-7 (PART-C): Transformer Networks

CS671_Online Lecture-7 (PART-B): Transformer Networks

CS671_Online Lecture-7 (PART-B): Transformer Networks

CS671_Online Lecture-7 (PART-A): Transformer Networks

CS671_Online Lecture-7 (PART-A): Transformer Networks

CS671_Online Lecture-6 (PART-B): Siamese Networks

CS671_Online Lecture-6 (PART-B): Siamese Networks

CS671_Online Lecture-6 (PART-A): Siamese Networks

CS671_Online Lecture-6 (PART-A): Siamese Networks

Online teaching at IIT MANDI through IPAD using Zoom and Notability app

Online teaching at IIT MANDI through IPAD using Zoom and Notability app

CS671_Online Lecture-5 (PART-E): Generative Adversarial networks (GAN)

CS671_Online Lecture-5 (PART-E): Generative Adversarial networks (GAN)

CS671_Online Lecture-5 (PART-D): Generative Adversarial networks (GAN)

CS671_Online Lecture-5 (PART-D): Generative Adversarial networks (GAN)

CS671_Online Lecture-5 (PART-C): Generative Adversarial networks (GAN)

CS671_Online Lecture-5 (PART-C): Generative Adversarial networks (GAN)

CS671_Online Lecture-5 (PART-B): Generative Adversarial networks (GAN)

CS671_Online Lecture-5 (PART-B): Generative Adversarial networks (GAN)

CS671_Online Lecture-5 (PART-A): Generative Adversarial networks (GAN)

CS671_Online Lecture-5 (PART-A): Generative Adversarial networks (GAN)

CS671_Online Lecture-4 (PART-C): Variational Autoencoder (VAE)

CS671_Online Lecture-4 (PART-C): Variational Autoencoder (VAE)

CS671_Online Lecture-4 (PART-B): Variational Autoencoder (VAE)

CS671_Online Lecture-4 (PART-B): Variational Autoencoder (VAE)

CS671_Online Lecture-4 (PART-D): Variational Autoencoder (VAE)

CS671_Online Lecture-4 (PART-D): Variational Autoencoder (VAE)

CS671_Online Lecture-4 (PART-A): Variational Autoencoder (VAE)

CS671_Online Lecture-4 (PART-A): Variational Autoencoder (VAE)

Attention deficit hyperactivity disorder (ADHD), Graph Convolutional Networks (GCN)

Attention deficit hyperactivity disorder (ADHD), Graph Convolutional Networks (GCN)

Diffusion MRI (HARDI)

Diffusion MRI (HARDI)

River Flowing in You (By Sonu Nigam): Yiruma

River Flowing in You (By Sonu Nigam): Yiruma

CS671_Online Lecture-3 (PART-F): Object Detection: Region Proposal Network

CS671_Online Lecture-3 (PART-F): Object Detection: Region Proposal Network

CS671_Online Lecture-3 (PART-E): Object Detection: Faster RCNN

CS671_Online Lecture-3 (PART-E): Object Detection: Faster RCNN

CS671_Online Lecture-3 (PART-D): Object Detection: Fast RCNN

CS671_Online Lecture-3 (PART-D): Object Detection: Fast RCNN

CS671_Online Lecture-3 (PART-C): Object Detection: RCNN

CS671_Online Lecture-3 (PART-C): Object Detection: RCNN

CS671_Online Lecture-3 (PART-B): Object Detection: Region Proposals

CS671_Online Lecture-3 (PART-B): Object Detection: Region Proposals

CS671_Online Lecture-3 (PART-A): Object Detection: IOU and NMS

CS671_Online Lecture-3 (PART-A): Object Detection: IOU and NMS

CS671_Online LAB-1: Recurrent Neural Networks

CS671_Online LAB-1: Recurrent Neural Networks

CS671_Online Lecture-2 (PART-A): Object Detection

CS671_Online Lecture-2 (PART-A): Object Detection

CS671_Online Lecture-1 (PART-D): Recurrent Neural Networks

CS671_Online Lecture-1 (PART-D): Recurrent Neural Networks

CS671_Online Lecture-1 (PART-C): Recurrent Neural Networks

CS671_Online Lecture-1 (PART-C): Recurrent Neural Networks

CS671_Online Lecture-1 (PART-B): Recurrent Neural Networks

CS671_Online Lecture-1 (PART-B): Recurrent Neural Networks

CS671_Online Lecture-1 (PART-A): Recurrent Neural Networks

CS671_Online Lecture-1 (PART-A): Recurrent Neural Networks

CS671_Tutorial 2: Introduction to tensorflow 2.0

CS671_Tutorial 2: Introduction to tensorflow 2.0

CS671_Tutorial 3: Making CNN using tensorflow2.0

CS671_Tutorial 3: Making CNN using tensorflow2.0

CS671_Tutorial 1 (PART-C): Making CNN using Keras

CS671_Tutorial 1 (PART-C): Making CNN using Keras

CS671_Tutorial 1 (PART-B): Making CNN using Keras

CS671_Tutorial 1 (PART-B): Making CNN using Keras

CS671_Tutorial 1 (PART-A): Making CNN using Keras

CS671_Tutorial 1 (PART-A): Making CNN using Keras

WADL(2019)_Day05 Session11 : Generative Adversarial Networks

WADL(2019)_Day05 Session11 : Generative Adversarial Networks

WADL(2019)_Day05 Session10 : Variational Autoencoders

WADL(2019)_Day05 Session10 : Variational Autoencoders

WADL(2019)_Day03 Session08 : Sequence Modelling in Neural Networks, RNN

WADL(2019)_Day03 Session08 : Sequence Modelling in Neural Networks, RNN

WADL(2019)_Day03 Session07 : Object Detection & Localisation

WADL(2019)_Day03 Session07 : Object Detection & Localisation

WADL(2019)_Day03 Session06 : Convolutional Neural Networks (Part B)

WADL(2019)_Day03 Session06 : Convolutional Neural Networks (Part B)

WADL(2019)_Day02 Session05 - Fully Connected Layer & Convolutional Neural Network

WADL(2019)_Day02 Session05 - Fully Connected Layer & Convolutional Neural Network

WADL(2019)_Day02 Session04 - Hot Topics in Deep Learning & Intuition of Neural Networks

WADL(2019)_Day02 Session04 - Hot Topics in Deep Learning & Intuition of Neural Networks

WADL(2019)_Day01 Session03 - Introduction to Perceptron

WADL(2019)_Day01 Session03 - Introduction to Perceptron

WADL(2019)_Day01 Session02 - Introduction to Pattern Analysis and Machine Learning

WADL(2019)_Day01 Session02 - Introduction to Pattern Analysis and Machine Learning

WADL(2019)_Day01 Session01- Deep Learning : Introduction & Overview

WADL(2019)_Day01 Session01- Deep Learning : Introduction & Overview

Gan4

Gan4

CS671_Topic-18 (PART-C): Generatve Adversarial netwroks

CS671_Topic-18 (PART-C): Generatve Adversarial netwroks

CS671_Topic-18 (PART-B): Generatve Adversarial netwroks

CS671_Topic-18 (PART-B): Generatve Adversarial netwroks

CS671_Topic-18 (PART-A): Generative Adversarial networks

CS671_Topic-18 (PART-A): Generative Adversarial networks

CS671_Topic-17 (PART-E): Recurrent Neural Networks

CS671_Topic-17 (PART-E): Recurrent Neural Networks

CS671_Topic-17 (PART-D): Recurrent Neural Networks

CS671_Topic-17 (PART-D): Recurrent Neural Networks

CS671_Topic-17 (PART-C): Recurrent Neural Networks

CS671_Topic-17 (PART-C): Recurrent Neural Networks

CS671_Topic-17 (PART-B): Recurrent Neural Networks

CS671_Topic-17 (PART-B): Recurrent Neural Networks

CS671_Topic-17 (PART-A): Recurrent Neural Networks

CS671_Topic-17 (PART-A): Recurrent Neural Networks

Siamese Network

Siamese Network

CS671_Topic-12 (PART-C): Single Shot Multi Box Detector (SSD)

CS671_Topic-12 (PART-C): Single Shot Multi Box Detector (SSD)

CS671_Topic-14 (PART-A): Autoencoder

CS671_Topic-14 (PART-A): Autoencoder

CS671_Topic-15 (PART-D): Variational Autoencoder

CS671_Topic-15 (PART-D): Variational Autoencoder

CS671_Topic-15 (PART-C): Variational Autoencoder

CS671_Topic-15 (PART-C): Variational Autoencoder

CS671_Topic-15 (PART-B): Variational Autoencoder

CS671_Topic-15 (PART-B): Variational Autoencoder

CS671_Topic-15 (PART-A): Variational Autoencoder

CS671_Topic-15 (PART-A): Variational Autoencoder

Variational Autoencoder (WHY-Conclusion and Recap)

Variational Autoencoder (WHY-Conclusion and Recap)

Object detection-Rcnn

Object detection-Rcnn

Objectdetection-survey02

Objectdetection-survey02

Objectdetection-survey01

Objectdetection-survey01

Variational Autoencoder (WHY - Loss function)

Variational Autoencoder (WHY - Loss function)

Autoencoder-(Basics)

Autoencoder-(Basics)

Variational Autoencoder (What it does)

Variational Autoencoder (What it does)

Variational Autoencoder (WHY-Prerequisite)

Variational Autoencoder (WHY-Prerequisite)

Od1

Od1

CS671_Topic-12 (PART-B): Single Shot Multi Box Detector (SSD)

CS671_Topic-12 (PART-B): Single Shot Multi Box Detector (SSD)

CS671_Topic-11 (PART-F): Object Localization and Detection

CS671_Topic-11 (PART-F): Object Localization and Detection

CS671_Topic-12 (PART-A): Single Shot Multi Box Detector (SSD)

CS671_Topic-12 (PART-A): Single Shot Multi Box Detector (SSD)

CS671_Topic-11 (PART-E): Object Localization and Detection

CS671_Topic-11 (PART-E): Object Localization and Detection

CS671_Topic-11 (PART-D): Object Localization and Detection

CS671_Topic-11 (PART-D): Object Localization and Detection

CS671_Topic-11 (PART-C): Object Localization and Detection

CS671_Topic-11 (PART-C): Object Localization and Detection

CS671_Topic-11 (PART-B): Object Localization and Detection

CS671_Topic-11 (PART-B): Object Localization and Detection

CS671_Topic-11 (PART-A): Object Localization and Detection

CS671_Topic-11 (PART-A): Object Localization and Detection

CS671_Topic-10 (PART-J): Convolutional Neural Networks

CS671_Topic-10 (PART-J): Convolutional Neural Networks

CS671_Topic-10 (PART-I): Convolutional Neural Networks

CS671_Topic-10 (PART-I): Convolutional Neural Networks

CS671_Topic-10 (PART-H): Convolutional Neural Networks

CS671_Topic-10 (PART-H): Convolutional Neural Networks

CS671_Topic-10 (PART-G): Convolutional Neural Networks

CS671_Topic-10 (PART-G): Convolutional Neural Networks

CS671_Topic-10 (PART-F): Convolutional Neural Networks

CS671_Topic-10 (PART-F): Convolutional Neural Networks

CS671_Topic-10 (PART-E): Convolutional Neural Networks

CS671_Topic-10 (PART-E): Convolutional Neural Networks

CS671_Topic-10 (PART-D): Convolutional Neural Networks

CS671_Topic-10 (PART-D): Convolutional Neural Networks

CS671_Topic-10 (PART-C): Convolutional Neural Networks

CS671_Topic-10 (PART-C): Convolutional Neural Networks

CS671_Topic-10 (PART-B): Convolutional Neural Networks

CS671_Topic-10 (PART-B): Convolutional Neural Networks

CS671_Topic-10 (PART-A): Convolutional Neural Networks

CS671_Topic-10 (PART-A): Convolutional Neural Networks

CS671_Topic-9 (PART-B): Loss Functions and Back propagation

CS671_Topic-9 (PART-B): Loss Functions and Back propagation

CS671_Topic-9 (PART-A): Loss Functions and Back propagation

CS671_Topic-9 (PART-A): Loss Functions and Back propagation

CS671_Topic-8 : Initializations

CS671_Topic-8 : Initializations

CS671_Topic-6 (PART-B): Computational Graphs

CS671_Topic-6 (PART-B): Computational Graphs

CS671_Topic-6 (PART-A): Computational Graphs

CS671_Topic-6 (PART-A): Computational Graphs

CS671_Topic-7 (PART-B): Cross Entropy Loss and Activation Functions

CS671_Topic-7 (PART-B): Cross Entropy Loss and Activation Functions

CS671_Topic-7 (PART-A): Cross Entropy Loss and Activation Functions

CS671_Topic-7 (PART-A): Cross Entropy Loss and Activation Functions

CS671_Topic-5 (PART-B): Loss Functions and Optimization

CS671_Topic-5 (PART-B): Loss Functions and Optimization

CS671_Topic-5 (PART-A): Loss Functions and Optimization

CS671_Topic-5 (PART-A): Loss Functions and Optimization

CS671_Topic-4 (PART-B): Fully Connected Layer

CS671_Topic-4 (PART-B): Fully Connected Layer

CS671_Topic-4 (PART-A): Fully Connected Layer

CS671_Topic-4 (PART-A): Fully Connected Layer

CS671_Topic-3 (PART-C): Neural Networks

CS671_Topic-3 (PART-C): Neural Networks

CS671_Topic-3 (PART-B): Neural Networks

CS671_Topic-3 (PART-B): Neural Networks

CS671_Topic-3 (PART-A): Neural Networks

CS671_Topic-3 (PART-A): Neural Networks

CS671_Topic-2 (PART-C): Linear Classification

CS671_Topic-2 (PART-C): Linear Classification

CS671_Topic-2 (PART-B): Linear Classification

CS671_Topic-2 (PART-B): Linear Classification

CS671_Topic-2 (PART-A): Linear Classification

CS671_Topic-2 (PART-A): Linear Classification

CS671_Topic-1 (PART-B): Linear Regression

CS671_Topic-1 (PART-B): Linear Regression

CS671_Topic-1 (PART-C): Linear Regression

CS671_Topic-1 (PART-C): Linear Regression

CS671_Topic-1 (PART-A): Linear Regression

CS671_Topic-1 (PART-A): Linear Regression

CS671_Topic-1 (PART-H): Linear Regression

CS671_Topic-1 (PART-H): Linear Regression

CS671_Topic-1 (PART-I): Linear Regression

CS671_Topic-1 (PART-I): Linear Regression

CS671_Topic-1 (PART-G): Linear Regression

CS671_Topic-1 (PART-G): Linear Regression

CS671_Topic-1 (PART-F): Linear Regression

CS671_Topic-1 (PART-F): Linear Regression

CS671_Topic-1 (PART-E): Linear Regression

CS671_Topic-1 (PART-E): Linear Regression

CS671_Topic-1 (PART-D): #Linear_Regression

CS671_Topic-1 (PART-D): #Linear_Regression

Lecture-1 Basics of machine learning: Linear Regression, Part-A

Lecture-1 Basics of machine learning: Linear Regression, Part-A