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.
Transfer Learning in NLP and the Birth of the Transformers Library
Explore the origins of HuggingFace and Transformers library, delving into transfer learning in NLP, open-source models, and the impact of community-driven AI research and development.
The Future of Natural Language Processing
Explore transfer learning in NLP, covering model efficiency, generalization, fine-tuning, and inductive biases. Gain insights into current trends and future directions from HuggingFace's science lead.
Machine Learning for Healthcare Data
Explore machine learning applications in healthcare, focusing on chronic kidney disease, sepsis, and surgical outcomes, with insights on transfer learning and predictive modeling.
Neural Nets for NLP 2021 - Multilingual Learning
Explore multilingual learning in NLP, covering models, data balancing, parameter sharing, and cross-lingual transfer techniques for improved language processing across diverse languages.
CMU Neural Nets for NLP 2020 - Multitask and Multilingual Learning
Explore multitask and multilingual learning in NLP, covering methods, objectives, and challenges. Gain insights into cross-lingual transfer, data balancing, and zero-shot approaches.
CMU Multilingual NLP 2022 - Data-Driven Strategies for NMT
Explore data-driven strategies for neural machine translation, including evaluation methods, data augmentation techniques, and approaches for high and low-resource languages.
TorchVision Quick Start - Building an Image Classifier in 10 Minutes
Build an image classifier for orangutans and komodo dragons using PyTorch's torchvision library and a pretrained ResNet model. Learn to leverage pre-trained models for quick and effective computer vision tasks.
Sign Language Detection Tutorial with Tensorflow Object Detection
Learn to build a real-time sign language detection system using Python, OpenCV, and TensorFlow. Covers image collection, labeling, model training, and live detection implementation.
Real Time Sign Language Detection with Tensorflow Object Detection and Python - Deep Learning SSD
Learn to build a real-time sign language detection system using Tensorflow Object Detection and Python. Covers image collection, labeling, model training, and implementation for translating sign language in real-time.
Real Time Face Mask Detection with Tensorflow and Python - Custom Object Detection with MobileNet SSD
Learn to build a real-time face mask detector using TensorFlow and Python. Master image labeling, custom object detection, transfer learning, and implement a practical workflow for training and deployment.
A Friendly Introduction to Codeless Deep Learning with KNIME Analytics Platform
Explore codeless deep learning with KNIME Analytics Platform. Learn neural network basics, convolutional networks for computer vision, and build a classification model using KNIME's Keras integration.
Movement Pruning - Adaptive Sparsity by Fine-Tuning
Explore Movement Pruning, an adaptive sparsity technique for fine-tuning deep neural networks. Learn its advantages over Magnitude Pruning in transfer learning scenarios and its impact on model efficiency.
Big Transfer - General Visual Representation Learning
Explore pre-trained ResNet for visual tasks, learning about large model pre-training and effective fine-tuning techniques for improved performance across diverse datasets.
Chip Placement with Deep Reinforcement Learning
Deep reinforcement learning optimizes chip placement, outperforming human experts in speed and efficiency. This AI-driven approach learns from experience, generalizes to new designs, and minimizes power, performance, and area constraints.
POET - Endlessly Generating Increasingly Complex and Diverse Learning Environments and Solutions
Explore POET, an innovative algorithm that generates and solves increasingly complex challenges, fostering open-ended learning and diverse problem-solving capabilities through evolutionary methods and transfer learning.
Transfer Learning with TensorFlow - Live Coding and Explanation
Comprehensive live coding session on transfer learning with TensorFlow, covering model reuse, data processing, CNN architectures, and performance optimization techniques for efficient deep learning.
Supervised and Self-Supervised Transfer Learning With PyTorch Lightning
Explore supervised and self-supervised transfer learning techniques using PyTorch Lightning, comparing their implementation, training, and generalization capabilities in deep learning applications.
Inverse Reinforcement Learning
Explore inverse reinforcement learning, transfer learning, and apprenticeship learning techniques to uncover underlying reward functions and improve AI decision-making processes.
Feudal Networks for Hierarchical RL
Explore hierarchical reinforcement learning with FeUdal Networks, covering architecture, results, and applications in complex environments like Water Maze.
Towards Understanding Transfer Learning with Applications to Medical Imaging
Explore transfer learning in medical imaging, focusing on deep learning applications, performance evaluation, and feature similarity analysis using CCA. Insights on ImageNet models and chest X-rays included.