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Resources for data scientists and business leaders.

  • Explorium for Business

    Explorium for Business

    No other platform does it all: automatically join your data with a broad range of datasets, extract and select the best set of features, and build production-ready models.

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  • Understanding and Handling Data and Concept Drift

    Understanding and Handling Data and Concept Drift

    Over time, ML models start to lose predictive power due to a concept known as model drift. How can you spot data and concept drift and avoid it? Read more.

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  • Feature Generation: The Next Frontier of Data Science

    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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  • The Essential Guide to Feature Selection

    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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  • Support and Coverage – Data Integration Metrics You Should Know

    Support and Coverage – Data Integration Metrics You Should Know

    Data enrichment is a crucial step in the modeling process that data scientists tend to overlook due to the difficulty in finding and utilizing external sources.

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  • 5 Steps to Mine Hidden Gold Out of An External Data Source

    5 Steps to Mine Hidden Gold Out of An External Data Source

    Extracting gold from an external data source is all about data prep. Follow these five steps and you’ll be well on your way to creating golden enrichments.

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  • Learn to turn the "art" of feature generation into a science.

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  • Data Scientists and Augmented Data Discovery: A Match Made in Heaven

    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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  • It’s Official: Online Lenders Can No Longer Afford to Ignore Alternative Data

    It’s Official: Online Lenders Can No Longer Afford to Ignore Alternative Data

    You don’t know what you don’t know, as the old saying goes. But in the age of Big Data, you simply can’t afford to shrug off "unknown unknowns".

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  • Stay Inside The Lines: Coloring With Artificial Intelligence

    Stay Inside The Lines: Coloring With Artificial Intelligence

    Can you teach AI to color better than a human? Using a generative adversarial network we can certainly try.

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  • The Complete Guide For Data Acquisition

    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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  • Extend Your Machine Learning Pipeline With Your Prediction Outcome

    Extend Your Machine Learning Pipeline With Your Prediction Outcome

    Does your machine learning pipeline end after your model makes a prediction? If your answer is “yes,” it doesn’t have to be.

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  • GlassesUSA.com Uses Explorium to Grow Revenue by Double Digits

    GlassesUSA.com Uses Explorium to Grow Revenue by Double Digits

    GlassesUSA.com increased both conversion rate and order value with Explorium, which lead to a 15-20% increase in the per-session value for their affected segments.

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  • AI is Making BI Obsolete, and Machine Learning is Leading the Way

    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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  • Clustering — When You Should Use it and Avoid It

    Clustering — When You Should Use it and Avoid It

    Cluster analysis is an essential tool for data scientists but it shouldn’t be your only one. Discover when you should, and shouldn’t, use clustering.

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  • Explorium Solution Brief

    Explorium Solution Brief

    Explorium is the only full-stack solution that encompasses automated data enrichment, feature engineering, and predictive modeling.

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  • AI Across the Funnel: The Use Cases You’re Missing Out On

    AI Across the Funnel: The Use Cases You’re Missing Out On

    Building core operations around ML models has helped many companies thrive across many other verticals. Still, others wait to implement at a large scale. Why?

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  • The Top Six Must-Attend Data Science Conferences Coming in 2020

    The Top Six Must-Attend Data Science Conferences Coming in 2020

    These data science conferences will ensure your 2020 is packed with lots of learning and networking opportunities.

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  • Cracking The Stability of Feature Selection

    Cracking The Stability of Feature Selection

    Some feature selection strategies may perform well when created but tend to break when tested later, meaning that some features are unstable and may perform badly on new data.

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  • The Complete Guide to Decision Trees

    The Complete Guide to Decision Trees

    Decision trees are one of the most popular algorithms out there but how much do you really know about them? This technical deep-dive breaks down everything you need to know.

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  • 2020: The Year Data Dominates Data Science

    2020: The Year Data Dominates Data Science

    From data economy growth to KPI-driven DS teams, our data science predictions for 2020 are all about the data.

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