Trillion Parameter Models Are Here
Explore ZeRO-Infinity's breakthrough in training trillion-parameter ML models with limited GPUs, revolutionizing large-scale deep learning and expanding possibilities for AI researchers and practitioners.
Recreate Google Translate - Model Training
Explore model training and testing for Neural Machine Translation, recreating Google Translate using mT5 and Hugging Face. Practical implementation and demo of multilingual translations.
Let's Build GPT - From Scratch, in Code, Spelled Out
Comprehensive tutorial on building a GPT model from scratch, covering key concepts like self-attention, multi-headed attention, and transformer architecture. Includes practical coding examples and insights into modern language models.
Building Makemore - Building a WaveNet
Dive deep into building a WaveNet-like convolutional neural network, exploring torch.nn, and understanding the typical deep learning development process through hands-on implementation.
Building Makemore - Becoming a Backprop Ninja
Hands-on tutorial on manual backpropagation through a 2-layer MLP, enhancing understanding of gradient flow in neural networks for confident innovation and debugging.
Building Makemore - Activations & Gradients, BatchNorm
Explore MLP internals, activations, gradients, and BatchNorm. Learn to diagnose deep networks, understand training challenges, and implement modern techniques for improved performance.
Building Makemore - MLP
Implement a multilayer perceptron character-level language model, covering machine learning basics like model training, hyperparameter tuning, evaluation, and addressing under/overfitting.
The Spelled-Out Intro to Language Modeling - Building Makemore
Comprehensive tutorial on building a bigram character-level language model, covering tensor operations, neural networks, and PyTorch fundamentals for natural language processing tasks.
Intro to Neural Networks and Backpropagation - Building Micrograd
Step-by-step guide to neural networks and backpropagation, covering core concepts, implementation in Python, and practical exercises. Ideal for beginners with basic Python knowledge.
DETR- End-to-End Object Detection with Transformers - Paper Explained
Explore DETR, an innovative object detection approach using transformers. Learn about its architecture, matching loss, Hungarian algorithm, and impressive results in this comprehensive explanation.
DALL-E - Zero-Shot Text-to-Image Generation - Paper Explained
Explore OpenAI's DALL-E: a groundbreaking AI model that generates images from text descriptions, combining concepts in plausible ways and showcasing emergent image-to-image capabilities.
VQ-GAN - Taming Transformers for High-Resolution Image Synthesis - Paper Explained
Explore VQ-GAN's innovative approach to high-resolution image synthesis, combining modified VQ-VAEs with GPT-2 for impressive results. Learn about perceptual loss, adversarial techniques, and comparisons with other models.
VQ-VAEs - Neural Discrete Representation Learning - Paper + PyTorch Code Explained
Explore VQ-VAEs for neural discrete representation learning, covering key concepts, implementation details, and applications in generative modeling. Gain insights into this important AI technique.
Chip Placement with Deep Reinforcement Learning - Paper Explained
Explore deep reinforcement learning for efficient chip placement, covering RL agents, computer manufacturing, and edge graph neural networks. Gain insights into innovative AI applications in hardware design.
Non-Parametric Transformers - Paper Explained
Explore non-parametric transformers: innovative AI model for tabular data, relational reasoning, and causal mechanisms. Learn architecture, loss function, and connections to other neural networks.
Build a Simple Language Translation App Using Python for Beginners
Learn to build a language translation app using Python, Hugging Face Transformers, and Gradio. Covers installation, text translation with deep learning, and creating a lightweight ML app interface.
Deep Drowsiness Detection Using YOLO, Pytorch and Python
Learn to implement drowsiness detection using YOLO, PyTorch, and Python. Covers object detection, model fine-tuning, and real-time application for driver safety.
Pose Estimation with the Fastest Python Deep Learning Model - MoveNet Lightning
Learn to implement real-time pose estimation using MoveNet Lightning, a fast Python deep learning model. Covers installation, TFLite integration, rendering results, and OpenCV implementation.
Build a Grammar Correction Python App with Gramformer and Gradio
Learn to create a Python app for grammar correction using Gramformer and Gradio. Develop skills in deep learning, natural language processing, and app deployment for improved writing assistance.
Sign Language Detection Using Action Recognition with Python - LSTM Deep Learning Model
Learn to build a sign language detection system using action recognition, LSTM, and Python. Extract keypoints, create datasets, train deep learning models, and make real-time predictions for sign language interpretation.
Machine Learning Explainability & Bias Detection with Watson OpenScale
Learn to monitor, explain, and debias machine learning models using Watson OpenScale. Explore performance metrics, interpret predictions, and detect model drift for improved AI transparency and reliability.