scikit-learn Insights

What is scikit-learn?

Scikit-learn is a free software machine learning library for Python. It features various classification, regression and clustering algorithms, and is designed to interoperate with the Python numerical and scientific libraries NumPy and SciPy. It is commonly used for tasks like predictive data analysis, building and evaluating machine learning models, and performing statistical analysis on datasets.

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What other technologies are related to scikit-learn?

scikit-learn Competitor Technologies

TensorFlow

TensorFlow is a machine learning framework that offers similar capabilities to scikit-learn for building and training models, but with a focus on deep learning and neural networks.

mentioned alongside scikit-learn in 35% (61.4k) of relevant job posts

PyTorch

PyTorch is another machine learning framework, like TensorFlow, that competes with scikit-learn, particularly in the domain of deep learning and neural networks.

mentioned alongside scikit-learn in 32% (54.9k) of relevant job posts

Keras

Keras is a high-level API for building and training neural networks. It can be used as a competitor since Scikit-learn also has some neural network capabilities, though Keras focuses almost exclusively on neural nets. Can also be complementary by using Keras models with scikit-learn wrappers.

mentioned alongside scikit-learn in 47% (19.8k) of relevant job posts

XGBoost

XGBoost is a gradient boosting framework that offers similar functionality to scikit-learn's gradient boosting methods and can be considered a competitor due to its widespread adoption and performance.

mentioned alongside scikit-learn in 60% (5.6k) of relevant job posts

SparkML

SparkML is Apache Spark's machine learning library, offering scalable machine learning algorithms, making it a competitor for large datasets where scikit-learn might be limited.

mentioned alongside scikit-learn in 64% (3.6k) of relevant job posts

statsmodels

statsmodels is a Python library that provides classes and functions for estimating and testing statistical models. Although complementary at times, it offers statistical modeling capabilities which are similar to those found in scikit-learn, thereby also making it a competitor.

mentioned alongside scikit-learn in 81% (1.6k) of relevant job posts

MXNet

MXNet is a deep learning framework that offers similar capabilities to scikit-learn for building and training models, particularly neural networks, making it a competitor.

mentioned alongside scikit-learn in 40% (2.6k) of relevant job posts

LightGBM

LightGBM is a gradient boosting framework, similar to XGBoost, and competes with scikit-learn's gradient boosting methods, known for its speed and efficiency.

mentioned alongside scikit-learn in 67% (1.4k) of relevant job posts

scikit-learn Complementary Technologies

Pandas

Pandas is a library for data manipulation and analysis, providing data structures like DataFrames that are often used as input to scikit-learn models.

mentioned alongside scikit-learn in 43% (40.9k) of relevant job posts

NumPy

NumPy is a fundamental library for numerical computing in Python, providing arrays and mathematical functions that scikit-learn relies on.

mentioned alongside scikit-learn in 48% (33k) of relevant job posts

SciPy

SciPy builds on NumPy and provides additional scientific computing tools and algorithms that can be used in conjunction with scikit-learn.

mentioned alongside scikit-learn in 56% (10.4k) of relevant job posts