Building a Real Time Sign Language Detection App with React.JS and Tensorflow.JS - Deep Learning
Learn to build a real-time sign language detection app using React.JS and TensorFlow.JS. Convert a Python model, host it, and create a standalone app with live detections in this hands-on deep learning tutorial.
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.
Real Time AI Gesture Recognition with Tensorflow.js + React.js + Fingerpose
Learn to build a real-time gesture recognition app using TensorFlow.js, React.js, and Fingerpose. Control web applications with hand gestures through deep learning-powered computer vision.
Real Time AI Hand Pose Estimation with Javascript, Tensorflow.js and React.js
Build a real-time hand pose estimation app using Javascript, TensorFlow.js, and React.js. Learn to set up a pre-trained model, use webcam input, and detect hand landmarks for gesture recognition applications.
Real Time AI Face Landmark Detection with Tensorflow.JS and React
Build a real-time facial landmark detection app using Tensorflow.JS and React. Learn to install models, create the app, and detect face points via webcam in just 20 minutes.
Build a Face Mask Detector with Watson and Python
Learn to create a face mask detector using Watson Visual Recognition, Python, and OpenCV. Capture images, visualize detections, and train custom object detection models in this hands-on tutorial.
Mean Average Precision Explained and PyTorch Implementation
Learn to calculate and implement Mean Average Precision (mAP) for evaluating object detection models, with a detailed explanation and hands-on PyTorch implementation from scratch.
Intersection Over Union Explained and PyTorch Implementation
Comprehensive guide to Intersection over Union (IoU) in object detection, covering theory and practical implementation in PyTorch. Ideal for understanding this crucial metric.
Comparing AI Image Caption Models: GIT, BLIP, and ViT+GPT2
Explore a comparison of three cutting-edge AI image captioning models, analyzing their performance across diverse images and understanding their unique approaches to vision-language tasks.
Stable Diffusion 2.0 Fine-Tuning with DreamBooth on Free Colab
Fine-tune Stable Diffusion 2.0 with DreamBooth on free Google Colab. Create custom AI avatars and profile pictures. Learn data collection, processing, model training, inference, and conversion for Automatic1111 compatibility.
Image Captioning Python App with ViT and GPT2 Using Hugging Face Models - Applied Deep Learning
Learn to create an image captioning app using ViT and GPT2 models from Hugging Face. Build a Gradio interface and deploy it on the Model Hub for easy access and sharing.
Zero-Shot Image Classification with OpenAI's CLIP Model
Explore OpenAI's CLIP model for zero-shot image classification, demonstrating its ability to predict relevant text for images using natural language instructions without task-specific training.
ESRGAN Paper Walkthrough
Detailed walkthrough of the ESRGAN paper, exploring enhanced super-resolution techniques using generative adversarial networks for improved image upscaling and restoration.
ESRGAN Implementation From Scratch
Learn to implement ESRGAN, an advanced image super-resolution technique, from scratch. Gain hands-on experience in deep learning and computer vision through step-by-step coding.
The Misinformation Age - Defending Against Deep Fakes
Explore deepfake technology's impact, current state, and initiatives to combat misinformation, including the Content Authenticity Initiative and hardware-level solutions for trusted content creation.
Batch Normalization in PyTorch - Adding Normalization to Convolutional Neural Network Layers
Learn to implement batch normalization in convolutional neural networks using PyTorch. Explore the benefits, create and compare networks, and optimize performance through hands-on coding and practical examples.
PyTorch DataLoader Source Code Debugging - Batch Building and Normalization
Debugging session exploring PyTorch DataLoader's inner workings, focusing on data normalization, batch building, and parameter impacts. Insights into efficient data handling for deep learning projects.
Object Detection with Transformers - From Training to Deployment
Explore cutting-edge object detection using transformers, from fundamental concepts to advanced techniques. Learn scalable training with Determined AI and deployment using MLflow.
Scalable AI for Environmental and Social Impact
Explore Microsoft's AI contributions to Apache Spark and Machine Learning, focusing on environmental and social impact projects like art exploration and endangered species protection.
Deep Learning Revolution: Turing Award Lecture by Geoffrey Hinton and Yann LeCun
Pioneers of deep learning discuss breakthroughs, applications, and future prospects of neural networks in AI, from handwriting recognition to medical imaging and autonomous vehicles.