Original article can be found here (source): Artificial Intelligence on Medium
Why Scikit-learn is Optimum for Python-based Machine Learning
Artificial intelligence (AI) and Machine Learning (ML) are capturing greater business value with powerful algorithms and functionalities. As an emerging AI development company, Oodles AI has witnessed a growing demand for cutting-edge AI solutions across markets. It has propelled the development of significant ML libraries, such as ‘Scikit-learn’ for machine learning applications like predictive analytics, sentiment analysis, and more.
This blog post analyzes the inside out of Scikit-learn and maps effective business applications with the comprehensive ML library.
Significance of Scikit-Learn for Python-based Machine Learning
Scikit-learn is a machine learning library developed in Python. It was initially started as a Google Summer of Code project by David Cournapeau in 2007. The name “Scikit” has its roots attached to the “SciPy”, a scientific computing library developed in 2001. Scikit-learn is developed on top of two such computational libraries and functions, namely SciPy, NumPy, and Matplotlib.
Today, global businesses like JP Morgan and Spotify use Scikit-learn’s ML algorithms, making it the most widely-used Python package.