The Keys to Effective Data Science Projects – Part 6: Feature Selection

We're in part six on our series of the Keys to Effective Data Science Projects. I won't cover basic Feature Engineering in this article - it's a huge topic and central to working in Machine Learning areas. I do recommend you check out as many articles as you can find on the subject, and once … Continue reading The Keys to Effective Data Science Projects – Part 6: Feature Selection

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The Keys to Effective Data Science Projects – Part 5: Update the Data

In this series on the “Keys to Effective Data Science Projects”, we've seen a process we can use, we've determined what we want to know, and we've ingested the data. In the last step we explored the data, and in a different way than we might be used to when working with in a database … Continue reading The Keys to Effective Data Science Projects – Part 5: Update the Data

The Keys to Effective Data Science Projects – Part 4: Explore the Data

We’re in a series on the “Keys to Effective Data Science Projects”. We've identified the question we want to solve, and made a preliminary pass at the data we need to answer that question. Next we brought in that data to a central location we can work with. We now want to explore that data. … Continue reading The Keys to Effective Data Science Projects – Part 4: Explore the Data

The Keys to Effective Data Science Projects – Part 3: Import Initial Data

We're in a series on the "Keys to Effective Data Science Projects" - and we've completed the hardest part - identifying the problem(s) we want to solve. Note that each problem gets it's own project - you're not going to predict when a hurricane will hit and how much money you'll get in your bonus … Continue reading The Keys to Effective Data Science Projects – Part 3: Import Initial Data