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The Essential Guide to Feature Selection
Feature selection is a key step in building powerful and interpretable machine learning models, but it’s also one of the easiest to get wrong.
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Data Scientists and Augmented Data Discovery: A Match Made in Heaven
Data science automation has historically focused on hyperparameter tuning and model optimization but now it’s time to see how new tools can empower data scientists to use more and better data.
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AI is Making BI Obsolete, and Machine Learning is Leading the Way
Why are we still hung up on BI? It’s time to embrace a paradigm that empowers us to make smarter, better predictions using real data with machine learning.
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The Complete Guide For Data Acquisition
This complete guide breaks down data acquisition into six steps, including data provider due diligence and data provider tests to uplift your model's accuracy.
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Ready to see Explorium in action?
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Feature Generation: The Next Frontier of Data Science
It's time to take feature generation - a subset of feature engineering - from an art to a science by opening up additional data sources to achieve breakthroughs in predictive models.
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