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Extract text from images in Python by comparing pytesseract, easyocr, and keras_ocr on the TextOCR dataset.
A live coding walkthrough of YOLOv8 object detection in Python, from image and webcam inference to car-driving video debugging.
Compare Python face-detection models for facial similarity, emotion and demographic analysis, keypoint detection, and face meshes through live coding.
Use Facebook Prophet in Python to forecast time series with nonlinear trends, multiple seasonalities, holiday effects, and evaluated predictions.
Explore chess game data with Python by analyzing ELO differences, PGN records, Stockfish results, and winning streaks.
Live coding a flight-delay dataset in Python: sourcing public data, cleaning it, exploring cancellation rates, and building Plotly visualizations.
Explore advanced XGBoost techniques for time series forecasting, including outlier removal, time-series cross-validation, lag features, and future prediction.
A speed benchmark compares Pandas with Ray, Dask, Modin, and Vaex on a large dataset.
Use Python simulations and graph loops to uncover the strategy behind the 100 prisoners riddle.
Forecast energy consumption with XGBoost by preparing time-series data, creating features, and examining feature importance in Python.
Learn to read, convert, display, annotate, and save video data with Python and OpenCV as a foundation for later machine-learning video tasks.
Build a Python sentiment classifier for Amazon reviews with NLTK VADER and Hugging Face RoBERTa, then compare the models’ results.
Analyze economic indicators with Python and pandas by retrieving FRED data, joining and cleaning datasets, and visualizing unemployment and participation trends.
Learn how cross-validation exposes overfitting and gives a more reliable estimate of a machine learning model’s predictive performance.
Learn to read, visualize, manipulate, filter, and save image arrays in Python using OpenCV and Matplotlib.
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