Pytorch Transformers from Scratch - Attention Is All You Need
Implement Pytorch Transformers from scratch, exploring the "Attention is all you need" paper. Learn attention mechanisms, encoder-decoder architecture, and practical application.
Pytorch Seq2Seq Tutorial for Machine Translation
Comprehensive tutorial on building a Seq2Seq model for German-English machine translation, covering implementation, training, and evaluation using PyTorch and the Multi30k dataset.
Pytorch TensorBoard Tutorial
Comprehensive guide to TensorBoard in PyTorch: plotting functions, hyperparameter search, image and weight visualization, and embedding projector. Practical examples included.
DALL-E Mini Explained - ML Coding Series
Comprehensive exploration of DALL-E mini, covering its architecture, components, and implementation details. Includes code walkthrough and explanations of key concepts in image synthesis.
Graph Attention Network Project Walkthrough
Comprehensive walkthrough of Graph Attention Network implementation, covering dataset analysis, key implementation details, and related deep learning projects for enthusiasts and practitioners.
Q Learning Tutorial - Training Loop
Explore the DQN training loop, covering policy implementation, reward calculation, and key steps in reinforcement learning algorithm implementation.
Q Learning Tutorial - Experience Replay
Explore Experience Replay in Q-Learning, focusing on data formatting and implementation. Learn key techniques for improving reinforcement learning algorithms in this hands-on tutorial.
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 - MLP
Implement a multilayer perceptron character-level language model, covering machine learning basics like model training, hyperparameter tuning, evaluation, and addressing under/overfitting.
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.
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.
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.
Reinforcement Learning - Full Course Using Python
Comprehensive introduction to reinforcement learning using Python, covering fundamentals, custom environments, and practical projects like Atari games and autonomous driving.
Deploy with FastAPI - Sentiment Analysis with BERT Using Huggingface, PyTorch, and Python Tutorial
Learn to deploy a pre-trained BERT model for sentiment analysis as a REST API using FastAPI, PyTorch, and Hugging Face. Covers project setup, API creation, model integration, and real-time predictions.
Sentiment Analysis with BERT Using Huggingface, PyTorch, and Python Tutorial
Learn to build a sentiment classification model using BERT, Hugging Face, and PyTorch. Covers BERT basics, fine-tuning for sentiment analysis, model training, evaluation, and prediction from raw text.
Sentiment Analysis with BERT Using Huggingface, PyTorch and Python Tutorial
Learn text preprocessing for sentiment analysis using BERT, Hugging Face, and PyTorch. Covers tokenization, padding, attention masks, dataset creation, and data splitting for NLP tasks.
Transfer Learning for Image Classification with PyTorch & Python Tutorial - Traffic Sign Recognition
Learn to classify traffic signs using transfer learning with PyTorch. Explore data, build datasets, train a pre-trained ResNet model, evaluate performance, and make predictions on new images.
LSTM Time Series Prediction Tutorial Using PyTorch in Python - Coronavirus Daily Cases Forecasting
Learn to forecast Coronavirus cases using LSTM and PyTorch. Covers data preprocessing, model building, training, evaluation, and future predictions with real-world time series data.
Build a Neural Network with Python Tutorial - Deep Learning with PyTorch
Learn to build, train, and evaluate a neural network for weather prediction using PyTorch. Covers data preprocessing, model architecture, GPU acceleration, and practical applications.
Build a Deep Q&A Web App with Transformers and Anvil - Python Deep Learning App
Learn to create a deep learning Q&A web app using Python, Transformers, and Anvil. Covers model loading, app development, integration, and deployment in a hands-on tutorial.
Implementing a Multi-Class CNN Image Classifier in Pytorch - Computer Vision Basics Ep. 3 CIFAR10 CNN
Learn to build a CNN image classifier using PyTorch and CIFAR10 dataset. Covers data loading, model architecture, training, and validation, with practical coding examples for computer vision enthusiasts.