Deep Learning

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PyTorch Day India 2026 Beyond the Brrr: Building a Unified Ecosystem for Optimized Kernels Aritra Ro

From RNN to Transformers | The Complete Attention Mechanism Series

How Images Convert to Input Tensors | Computer Vision Explained for AI Engineers

How Machines Read Handwriting

Lec 16. Generative Models: Conditional Models

Lec 15. Generative Models: Representation Learning Meets Generative Modeling

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NVIDIA DGX Spark vs RTX 4090 | LLM inference, training speed and more

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W&B Models end-to-end demo

Variational Autoencoder (VAE) | 10 Marks in 1 Minute | Generative AI

Transformer Architecture in Tamil | Encoder Decoder & Attention Explained | Deep Learning NLP

Neural Networks Explained: A Simple Analogy for ANN Concepts in AI

Complete AI/Machine Learning Course 2026 | GenAI + Multimodal Models | 12-Hour Live Class | Edureka

How Images Are Stored In Computers | RGB Matrix & Image Processing Explained

Residual Networks (ResNet) Explained Intuitively | Why Deep Networks Fail & How ResNet Fixes It

How RNNs Taught AI systems To Remember Things (Deep Learning Explained)

Keras Turns 10: A decade of deep learning

Understanding JAX: JIT, XLA, and Pure Functions Explained

The relationship between convolution & self-attention

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PyTorch Foundation Spotlight: Christian Jacobi

Stanford Dropout at 20, Amogh Chaturvedi raised $5Million in just 2 Days!!

How Residual Connections Are Getting an Upgrade [mHC]

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Lec 04. Architectures: Grids

Lec 10. Architectures: Memory

Lec 11. Representation Learning: Reconstruction-Based

Lec 14. Generative Models: Basics

Lec 12. Representation Learning: Similarity-Based

Lec 19. Transfer Learning: Data

PyTorch Tutorial

Lec 18. Transfer Learning: Models

GAN Exam concept | 10 marks in 1 Minute

How to use KerasHub with Hugging Face

3: Deep Learning for Computer Vision – Building Convolutional Neural Networks from Scratch

8: Deep Learning for Natural Language – Transformers, Self-Supervised Learning

2: Training Deep NNs (cont.); Introduction to Keras/Tensorflow; Application to Tabular Data

4: Deep Learning for Computer Vision – Transfer Learning and Fine-Tuning; Intro to HuggingFace

11: Generative AI – Text-to-Image Models

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