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Build a deployable Q&A web app that uses a RoBERTa transformer to extract answers from user-provided text and questions.
Build a reinforcement learning agent that plays Doom using VizDoom, OpenAI Gym, PPO, reward shaping, and curriculum learning.
Build and train a Python reinforcement learning model that learns to play Super Mario by preprocessing game frames and using the PPO algorithm.
Apply and tune Canny edge detection in OpenCV using grayscale preprocessing, Gaussian blur, image resizing, and result export.
Build a real-time TikTok analytics dashboard with Python, ETL preprocessing, hashtag search, and interactive Streamlit visualizations.
Access webcams and USB capture devices in real time with Python and OpenCV, including device selection, photo capture, and live video display.
Build a facial verification app from a Siamese neural network, training it with TensorFlow and integrating the model into a Kivy application.
Build a real-time facial verification app by integrating a trained Siamese neural network model with Kivy, TensorFlow, and a webcam.
Real-time facial verification with OpenCV: build a verification function, tune detection and verification thresholds, and test a Siamese neural network through a webcam.
Evaluate a Siamese neural network for facial verification using predictions, precision and recall, visualization, and model saving and reloading.
Train a Siamese neural network for facial recognition by building its loss function, optimizer, custom training step, and training loop.
Implement a Siamese neural network for face verification with image embeddings, an L1 distance layer, and Keras’s Functional API.
Collects LFW negative images and webcam-based anchor and positive samples for a Siamese neural network facial verification app.
Set up TensorFlow and folder structures for a deep-learning facial verification app, including GPU-growth configuration.
Use Hugging Face Transformers and Python to generate concise summaries of Wikipedia, news, and scientific articles with Pegasus.
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