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This is an interactive notebook-based course that teaches machine learning from Python fundamentals through deep learning and natural language processing. It uses real datasets and multiple frameworks within a structured, hands-on curriculum that combines concise explanations with executable code cells, built-in datasets, and embedded exercise checkpoints. Learning progresses through data preparation and exploration, classical machine learning workflows, computer vision with convolutional neural networks, and natural language processing with deep learning, all delivered as a cohesive progressi
This project is a comprehensive pandas data analysis tutorial and instructional guide designed for learning data manipulation and analysis. It serves as a tabular data processing guide and a manual for time series analysis, providing a structured approach to cleaning, merging, and transforming datasets. The repository functions as a data feature engineering course, providing tutorials on constructing and selecting dataset features to improve machine learning model performance. It also includes a vectorized data operations guide for performing element-wise mathematical computations and matrix
Python package implementing ML feature engineering and pre-processing for polars or pandas dataframes.
tsfresh is an automated feature engineering tool and library designed to extract statistical characteristics from raw time series data. It transforms sequential data into tabular datasets, converting time series into a flat format where each row represents a unique entity and columns represent extracted features. The project distinguishes itself through a parallel data processing framework that distributes heavy computational workloads across multiple CPU cores. It also implements hypothesis-based feature selection to identify the most predictive characteristics and filter out irrelevant ones
The main features of hbldh/pyefd are: Feature Engineering.
Projects with overlapping indexed features include: nyandwi/machine_learning_complete — This is an interactive notebook-based course that teaches machine learning from Python fundamentals through deep… datawhalechina/joyful-pandas — This project is a comprehensive pandas data analysis tutorial and instructional guide designed for learning data… azukds/tubular — Python package implementing ML feature engineering and pre-processing for polars or pandas dataframes. chasedehan/boostaroota — A fast xgboost feature selection algorithm. chrislemke/sk-transformers — A collection of pandas & scikit-learn compatible transformers for preprocessing and feature engineering 🛠. blue-yonder/tsfresh — tsfresh is an automated feature engineering tool and library designed to extract statistical characteristics from raw…