Understanding Convolution Kernels for CNNs - Computer Vision Basics - What Are Convolutions?
Explore convolutional kernels in CNNs, from basic concepts to practical applications in PyTorch. Learn visualization techniques and understand their impact on computer vision tasks.
Image Classification with CIFAR 10 - Computer Vision Basics Ep. 1 Loading Data
Practical guide to image classification using CIFAR10 dataset. Learn to load data, create DataLoaders, transform images, and visualize the dataset in PyTorch for computer vision tasks.
Hugging Face Transformers - The Basics - Practical Coding Guides - NLP Models (BERT/RoBERTa)
Learn the basics of Hugging Face Transformers library, including installation, pre-defined pipelines, and implementing models in PyTorch. Explore tokenization, attention masks, and model outputs in this practical coding guide.
Build Your First Model with PyTorch and Python - PyTorch Tutorial for Beginners
Learn to implement a Simple Linear Regression model using PyTorch, covering data exploration, model creation, tensor conversion, training, and prediction analysis in this beginner-friendly tutorial.
Mastering PyTorch Tensors- The Ultimate Guide for Beginners
Comprehensive guide to PyTorch tensors: creation, types, operations, indexing, reshaping, and data handling. Essential for beginners in machine learning and deep learning projects.
Getting Started with PyTorch Lightning for Deep Learning
Explore PyTorch Lightning for easier Deep Learning projects, using Google's GoEmotions dataset to build an emotion classification model with practical coding examples.
Create YOLO Dataset for Custom Object Detection Using OpenCV, PyTorch, and Python Tutorial
Learn to create custom datasets for YOLOv5 object detection, focusing on clothing items in images using OpenCV, PyTorch, and Python. Includes dataset preparation, format conversion, and file structure explanation.
Multi-Label Classification on Unhealthy Comments - Finetuning RoBERTa with PyTorch - Coding Tutorial
Learn to finetune RoBERTa for multi-label classification of unhealthy comments using PyTorch Lightning. Practical coding guide covers data preparation, model creation, training, and evaluation.
Supercharge Your Training With PyTorch Lightning and Weights & Biases
Learn to enhance ML pipelines using PyTorch Lightning and Weights & Biases. Discover efficient experiment tracking, advanced logging techniques, and how to leverage callbacks for improved model development and visualization.
Convolutional Neural Nets Explained and Implemented in Python - PyTorch
Comprehensive guide to Convolutional Neural Networks: theory, implementation, and practical applications using Python and PyTorch for computer vision tasks like image classification.
AlexNet and ImageNet Explained
Explore the revolutionary AlexNet CNN and ImageNet dataset, their impact on deep learning, and practical implementation using PyTorch for image classification tasks.
Fine-Tune High Performance Sentence Transformers With Multiple Negatives Ranking
Learn to fine-tune sentence transformers using multiple negatives ranking loss, improving embedding quality for similarity prediction and outperforming SBERT. Includes PyTorch and sentence-transformers library implementations.
Fine-Tune Sentence Transformers the OG Way - With NLI Softmax Loss
Explore fine-tuning sentence transformers using NLI softmax loss. Learn preprocessing, PyTorch implementation, and Sentence-Transformers library usage for improved sentence embeddings in NLP applications.
PyTorch Crash Course - Getting Started with Deep Learning
Comprehensive introduction to PyTorch, covering tensor basics, autograd, linear regression, neural networks, and CNNs. Ideal for beginners in deep learning.
Building a GAN From Scratch With PyTorch - Theory + Implementation
Learn to build a Generative Adversarial Network from scratch using PyTorch and PyTorch Lightning, covering theory, implementation, and testing in this comprehensive tutorial.
Long Short-Term Memory with PyTorch + Lightning
Learn to implement and train LSTM networks using PyTorch and Lightning, covering custom LSTM coding, PyTorch's built-in LSTM, and advanced training techniques for deep learning projects.
Introduction to Coding Neural Networks with PyTorch and Lightning
Aprenda a codificar redes neurais eficientemente com PyTorch e Lightning, simplificando o processo, melhorando a portabilidade e otimizando a taxa de aprendizagem automaticamente.
Introduction to PyTorch
Learn to create, visualize, and optimize a neural network using PyTorch in this step-by-step tutorial, covering network creation, output graphing, and parameter optimization through backpropagation.
Neural Style Transfer - From Theory to Pytorch Implementation
Explore neural style transfer using PyTorch, from theory to implementation. Learn to manipulate photos with deep neural networks, creating stunning AI-generated artwork.
Efficient Geometry-Aware 3D Generative Adversarial Networks - EG3D
Hands-on guide to using pre-built EG3D models on Ubuntu 22.04 with Python 3.9, PyTorch, and CuDA GPU libraries. Learn to visualize, export, and generate 3D shapes from various models.
TorchStudio - Deep Learning Toolkit
Hands-on guide to TorchStudio: Access PyTorch datasets, train models, and compare results. Ideal for beginners and experienced users in the PyTorch ecosystem.