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Top Data Science Tools That Will Empower Your Data Exploration Processes

datapine

Data science has become an extremely rewarding career choice for people interested in extracting, manipulating, and generating insights out of large volumes of data. To fully leverage the power of data science, scientists often need to obtain skills in databases, statistical programming tools, and data visualizations.

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Data science vs data analytics: Unpacking the differences

IBM Big Data Hub

Though you may encounter the terms “data science” and “data analytics” being used interchangeably in conversations or online, they refer to two distinctly different concepts. Meanwhile, data analytics is the act of examining datasets to extract value and find answers to specific questions.

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Data Science, Past & Future

Domino Data Lab

Paco Nathan presented, “Data Science, Past & Future” , at Rev. This blog post provides a concise session summary, a video, and a written transcript. data science’s emergence as an interdisciplinary field – from industry, not academia. He was saying this doesn’t belong just in statistics.

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Change The Way You Do ML With Applied ML Prototypes

Cloudera

Today’s enterprise data science teams have one of the most challenging, yet most important roles to play in your business’s ML strategy. In our current landscape, businesses that have adopted a successful ML strategy are outperforming their competitors by over 9%. Explaining Models with LIME and SHAP.

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Smarten Announces SnapShot Anomaly Monitoring Alerts: Powerful Tools for Business Users!

Smarten

Contact the Smarten team to find out more about Smarten SnapShot Anomaly Monitoring and how this powerful functionality can help you to gain insight into your data and results.

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Smarten Augmented Analytics Receives CERT-IN Certification for Its Products and Services!

Smarten

Contact the Smarten team for more information on Smarten Augmented Analytics solution. The Smarten approach to business intelligence and business analytics focuses on the business user and provides Advanced Data Discovery so users can perform early prototyping and test hypotheses without the skills of a data scientist.

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PASS Financials: past, present and the Future:

Jen Stirrup

My analysis is based on the Financial statements put forward by PASS using some basic metrics; until you do that piece, you can’t move forward to compare and contrast it with other data since you have not done your ‘descriptive statistical analysis’ first to ensure that the comparison is valid. What does that say about the #SQLFamily?

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