Google Scikit-learn

Scikit-learn was created in 2007 by David Cournapeau as a Google Summer of Code project. It was later developed by a team of contributors to provide accessible machine learning tools for Python users. The library aimed to simplify the implementation of machine learning algorithms and facilitate data analysis and mining tasks.

Strengths of Scikit-learn include its simplicity, extensive documentation, and integration with other Python libraries. Weaknesses involve limitations in handling very large datasets and deep learning tasks. Competitors include TensorFlow, PyTorch, and XGBoost.

A Scikit-learn expert must have strong proficiency in Python programming, knowledge of machine learning algorithms, experience with data preprocessing and feature engineering, and familiarity with NumPy and SciPy libraries. They should also understand model evaluation techniques and hyperparameter tuning.