Remove Data Warehouse Remove Deep Learning Remove Optimization Remove Predictive Modeling
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Rapidminer Platform Supports Entire Data Science Lifecycle

David Menninger's Analyst Perspectives

Rapidminer is a visual enterprise data science platform that includes data extraction, data mining, deep learning, artificial intelligence and machine learning (AI/ML) and predictive analytics. Rapidminer Studio is its visual workflow designer for the creation of predictive models.

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Data science vs. machine learning: What’s the difference?

IBM Big Data Hub

Data from various sources, collected in different forms, require data entry and compilation. That can be made easier today with virtual data warehouses that have a centralized platform where data from different sources can be stored. One challenge in applying data science is to identify pertinent business issues.

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10 everyday machine learning use cases

IBM Big Data Hub

Machine learning in marketing and sales According to Forbes , marketing and sales teams prioritize AI and ML more than any other enterprise department. Marketers use ML for lead generation, data analytics, online searches and search engine optimization (SEO). Computer vision fuels self-driving cars.

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Of Muffins and Machine Learning Models

Cloudera

This allows data scientists, engineers and data management teams to have the right level of access to effectively perform their role. By logging the performance of every combination of search parameters within an experiment, we can choose the optimal set of parameters when building a model.

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Topics to watch at the Strata Data Conference in New York 2019

O'Reilly on Data

For example, even though ML and ML-related concepts —a related term, “ML models,” (No. Deep learning,” for example, fell year over year to No. But the database—or, more precisely, the data model —is no longer the sole or, arguably, the primary focus of data engineering. 719, trailing "data warehouse."

IoT 20
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The Cloud Connection: How Governance Supports Security

Alation

Similar to a data warehouse schema, this prep tool automates the development of the recipe to match. Organizations launched initiatives to be “ data-driven ” (though we at Hired Brains Research prefer the term “data-aware”). Automatic sampling to test transformation. Scheduling. Target Matching.