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Based on our record, MLlib seems to be more popular. It has been mentiond 2 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
The MLlib library gives us a very wide range of available Machine Learning algorithms and additional tools for standardisation, tokenisation and many others (for more information visit the official website Apache Spark MLlib). (Apache Spark Machine Learning predicting diabetes in patients). Source: about 2 years ago
Totally agree with the current responses, especially for the purposes of understanding exactly what's going on under the hood, but did want to just call out the fact that you can simply use a machine learning library that's implemented in a distributed way. Examples would be MLlib From Spark and h2o. H2O in particular will take care of pretty much everything for you in terms of initializing a cluster, and has a... Source: over 2 years ago
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
NumPy - NumPy is the fundamental package for scientific computing with Python
OpenCV - OpenCV is the world's biggest computer vision library
Dataiku - Dataiku is the developer of DSS, the integrated development platform for data professionals to turn raw data into predictions.
Exploratory - Exploratory enables users to understand data by transforming, visualizing, and applying advanced statistics and machine learning algorithms.