ML

Data Science Work Environment

Beyond Supervised Learning: Accelerating Business Insights with Reinforcement Learning

Beyond Supervised Learning: Accelerating Business Insights with Reinforcement Learning Author: Evie Fowler Data science – the art of using data to draw insight and inferences around the way the world works – is a crucial component of business today. The modern business world is dynamic and fast-paced, though, and organizations that spend too much time […]

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A Hybrid Approach to Customer Segmentation: Combining Machine Learning and Rules-Based Methodologies

A Hybrid Approach to Customer Segmentation: Combining Machine Learning and Rules-Based Methodologies Author: Evie Fowler Customer segmentation refers to the process of dividing customers into subgroups with similar buying habits and needs. It helps businesses understand their customers better so that they can market existing products more effectively and even develop new products to meet

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MLOps: Building Machine Learning Systems

MLOps: Building Machine Learning Systems Author: Ani Madurkar The importance of thinking larger when designing effective and ethical machine learning systems MLOps is taking the data science and machine learning landscape by storm as organizations struggle to realize the value promised by their data. This is partly due to the difficulty in productionizing machine learning

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Improving Data Quality: Anomaly Detection Made Simple

From business managers, to data scientists, to UX developers — anyone who works with data knows anomalies can be a chore to find and an even bigger chore to resolve. Incorrect or faulty data can cause a business to miss revenue opportunities or potentially make poor business decisions based on erroneous analysis. For organizations whose

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AI vs. Machine Learning: What’s The Difference?

Artificial intelligence, or “AI”, is a buzzword that has been around for decades… but what does itreallymean? For most people, it can be hard to differentiate between the futuristic sounding AI and its less glamorous sounding counterpart, machine learning, sometimes called “ML”.  Even Fulcrum’s Data Scientists agree, that while the average person interacts with some

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