Deep Learning

Lecture 3 : Additive Attention Explained Simply | Step-by-Step for Beginners

PyTorch vs Tensorflow F vs Keras

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

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

Want to Be a Data Scientist? Follow This Roadmap! #shorts #simplilearn

Complete AI Engineer Roadmap 2026 | From Beginner to Pro #simplilearn #shorts

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

How Residual Connections Are Getting an Upgrade [mHC]

Why I Quit My Stable Job in Tech In My 20s

Gen AI and ML Full course in 11 Hours [ 2026 | Gen Ai and Ml for beginner | Edureka Live

VGG-16 Architecture Visually Explained

Transformer Encoder Architecture Explained

Why the BERT Model Is a Game-Changer for Language Models

AI Roadmap Explained | From Basics to Building a Mini Chatbot (Transformers Series)

I Visualized a Decoder-Only Transformer

This is what LLMs really store

Transfer Learning in Deep Learning Tamil | Brain Tumor Segmentation using VGG16 | Adi Explains

10. Transformers & Attention Mechanisms Explained: Q, K, and V | In Hindi

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

How to use KerasHub with Hugging Face

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

Generative AI Roadmap for 2026 | How to Become GenAI Expert #shorts #simplilearn

Deep Learning With TensorFlow and Keras [FREE] | TensorFlow Tutorial | Keras Tutorial | Simplilearn

Deep Learning With TensorFlow and Keras [FREE] | TensorFlow Tutorial | Keras Tutorial | Simplilearn

AlexNet Explained from Scratch | Architecture, Layers, ReLU, Dropout

LeNet-5 CNN Architecture Explained | The Network That Started Deep Learning