Build a Deep Facial Recognition App - Real Time Predictions with OpenCV - Python
Learn to implement real-time facial recognition in Python using OpenCV, including setting up verification images, building a verify function, and performing recognition with webcam integration.
Build a Deep Facial Recognition App - Making Facial Recognition Predictions - Python
Learn to implement facial recognition in Python using Siamese Neural Networks, including making predictions, calculating metrics, and saving/reloading the model for real-world applications.
Build a Deep Facial Recognition App - Training a Siamese Neural Network - Python
Learn to train a Siamese Neural Network for facial recognition using Python and TensorFlow. Covers loss functions, optimizers, custom training steps, and model training implementation.
Build a Deep Facial Recognition App - Building a Siamese Neural Network - Python
Learn to build a Siamese Neural Network for facial recognition using TensorFlow, including image embedding, L1 distance layer, and model integration in a Kivy app.
Build a Deep Facial Recognition App - Collecting Data - Deep Learning Project Tutorial
Learn to build a deep facial recognition app by collecting and processing data, using OpenCV for webcam access, and preparing images for model training.
Build a Deep Facial Recognition App from Paper to Code - Deep Learning Project Tutorial
Learn to build a deep facial recognition app using TensorFlow, from setting up dependencies to creating data structures. Implement Siamese Neural Networks for one-shot image recognition in this hands-on tutorial.
Getting Started with AI Powered Q&A Using Hugging Face Transformers - HuggingFace Tutorial
Learn to implement AI-powered Q&A using Hugging Face Transformers. Explore BERT, transfer learning, and practical coding with pre-trained models for your own data and solutions.
Stress Testing Qdrant - Semantic Search with 90,000 Vectors - Lightning Fast Search Microservice
Explore stress testing Qdrant for semantic search with 90,000 vectors. Learn to set up TensorFlow, generate data, and evaluate search efficiency in this hands-on tutorial.
Probabilistic Deep Learning in TensorFlow - The Why and How - ODSC Europe 2019
Explore probabilistic deep learning in TensorFlow, focusing on Bayesian techniques, uncertainty modeling, and practical applications using TensorFlow Probability for more robust and interpretable neural networks.
Word Embedding with Keras - A RStudio Tutorial
Learn word embedding techniques using Keras in RStudio. Covers theory, concepts, and practical implementation, including Keras basics and machine learning fundamentals for natural language processing.
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.
Create and Visualize Your First Perceptron and Feed Forward Network in Python
Learn to build and visualize Perceptron and Feed Forward networks in Python using Keras and TensorFlow. Ideal for beginners, this hands-on tutorial covers network creation, visualization, and fundamental deep learning concepts.
Create and Visualize Your Very First Neural Network in Python
Create and visualize your first neural network in Python using Keras and TensorFlow. Learn step-by-step, from basic concepts to building a sequential model, with helpful visualizations and a pre-trained network example.
Self-Driving Apps - Using Machine Learning and AI to Improve App Performance
Explore machine learning in apps with examples from Instacart. Learn how AI enhances performance, improves logistics, and drives growth in mobile applications.
Creating an Animal Segmentation Model with U-Net and TensorFlow Keras
Learn to implement and train a U-Net model for animal segmentation using TensorFlow/Keras. Covers data preprocessing, model architecture, training, and evaluation with practical code examples.
How to Code a Machine Learning Lip Reading App with Python Tensorflow and Streamlit
Learn to build a lip-reading application using Python, TensorFlow, and Streamlit. Gain hands-on experience in machine learning and computer vision while creating a practical, cutting-edge project.
Build a Deep Learning Model That Can Lip Read Using Python and Tensorflow
Learn to create a deep learning model for lip reading using Python and TensorFlow in this comprehensive tutorial, covering data preparation, model architecture, and implementation techniques.
Building an ML Cancer Segmentation API in 15 Minutes
Build and deploy a machine learning Cancer Segmentation API using Python, TensorFlow, FastAPI, and Heroku in a quick tutorial. Learn to create a practical ML application for medical imaging analysis.
Uncover What Deep CNNs Are Doing With Python and Tensorflow
Visualize CNN layer outputs using Python and TensorFlow to understand how computer vision models make predictions, with step-by-step guidance and code examples.
Tensorflow Multi-Person Pose Estimation with Python - Machine Learning Tutorial
Learn to implement multi-person pose estimation using TensorFlow and Python. Explore MobileNetv2, Feature Pyramid Networks, and CenterNet concepts in this hands-on machine learning tutorial.
Deep Reinforcement Learning for Atari Games Python Tutorial - AI Plays Space Invaders
Learn to build AI models that play Space Invaders using Python, OpenAI Gym, and TensorFlow. Explore reinforcement learning techniques to create autonomous game-playing agents and improve your coding skills.