Most Popular Data Science Software Tools

Data Science Software Tools

• Algorithms.io is one of the most popular data science platforms that make streaming analytics simple and easy.
• It’s an intelligent platform optimized for real time classification of streaming data from apps, devices and sensor.
• Raw information gathered from various resources could be turned into usable information and apply machine learning for streaming information.
• It simplifies machine learning process by addressing issues like scalability, security and infrastructure.

• Apache graph is used to perform graph processing on data. It uses Hadoop’s MapReduce implementation to process graph.
• Giraph is an open-source project and it uses bulk synchronous parallel model of distributed computing.
• Apache graph is best choice for unleashing the potential of structured datasets at massive scale.

• Rapidminer is a software platform for data science that could be used for data prep, machine learning and predictive model deployment.
• It offer features like code free workflow, seamless transformation of raw data into usable one.
• With Rapideminer you can connect to any data source, any format, at any scale.
• Data scientists can quickly discover patterns and issues with data quality.
• Clean data for advanced algorithm, create optimal data that used for predictive analysis.

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• Data robot offers an automated machine learning platform to transform raw data into organized data useful for predictive analysis.
• DataRobot automates entire modeling lifecycle, enabling users to quickly and easily build accurate predictive models.
• DataRobot automatically searches through millions of combination of algorithms, data preprocessing steps, transformations, features and tuning parameters for the best machine learning model.
• DataRobot offers parallel modeling engine that can build and tune machine learning models.
• The intuitive web-based interface allows anyone to interact with powerful platform irrespective of machine learning experience.
• It offers best-in-class algorithms from R, Python, H20, Spark, and other sources, giving users the best set of analytics tools for predictive challenges.

• Apache Hadoop is an open source programming framework that is used for processing big data sets. It uses MapReduce programming model while dealing with big data.
• Hadoop manges data whether it’s structured or unstructured and in any other format.
• It’s extremely scalable where one can easily add new nodes for adding new volumes of data.
• Hadoop uses parallel processing method that is the reason it can process high volumes of data with ease.
• From small to large organizations any one could use Hadoop for data processing.