Lack of collaboration between team members could be a frustrating experience as could be spending time maintaining your models after deploying them.
These reasons among others could mean the need for adopting data science platforms and having to choose the right platform from a host of available packages in the market.
“Various organizations keep floating data science platforms to simplify machine learning workflows. However, in the ever-changing data science landscape, only a few draw the attention of practitioners,” says a report.
Here is a list of top 7 data science platforms available for use in 2020.
Databricks
“Built by the founder of Apache Spark, Databricks provides a unified analytics platform that allows data scientists to manage end-to-end machine learning workflows.
The one-size-fits-all platform not only enables practitioners to explore, visualize and build superior machine learning models, but also allows them to scale it quickly with the help of collaboration.”
DataRobot
DataRobotassists companies to automate the workflows of machine learning through its feature-rich solutions and it constantly strives to enhance its platform by either acquiring various companies, or by developing in-house solutions.
“Apart from assisting the regular analytics workflows”, DataRobot is among the best in the AutoML arena.
Apache Spark
“Apache Spark is an open-source unified analytics engine for large-scale data processing and analyzing. It is similar to HadoopMapReduce; it works on cluster computing, but due to exceptional speed – which is believed to be 100x faster in memory and 10x faster on disk than Hadoop – it has become popular among data scientists.”
Dataiku
This is yet another reputed enterprise AI and machine learning platform that “helps businesses in minimizing data processes to expedite the development of machine learning-based solutions”.
The platform helps companies in bringing together data analysts, engineers, and scientists to achieve shared goals through collaboration. “It also provides instant visual and statistical feedback on model performance to manage models’ lifecycle effectively”.
IBM Cloud Pak for Data
“Built on Red Hat OpenShift container platform, IBM Cloud Pak for Data is a fully-integrated AI platform to meet the changing needs of enterprises. It allows data scientists to unlock insights and eliminate data silos quickly.
The platform has a high degree of enterprise readiness and delivers business value by enabling practitioners to integrate with other platforms using APIs.”
Alteryx
“Alteryx is a self-service analytics platform that can be utilized across organizations to democratize data. The platform caters to every need of analytics professionals, such as business intelligence, data analyst, data scientist, and non-experts to assist them in quickly solving business problems. It supports analytics modelling without code and advanced modelling with algorithms.”
TIBCO
TIBCO Software acts as a foundation for digital innovation for data-driven companies. “Integration among platforms has been one of the longest standing predicaments for organizations.”
“Thus, TIBCO offers a suite of products like Connect, API-Led Integration, Data Fabric, Unify, Data Science & Streaming, and more, to eliminate challenges for a streamlined data science workflow.”
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