The Keys to Effective Data Science Projects – Part 9: Testing and Validation

We’re continuing our discussion of the series of the Keys to Effective Data Science Projects,  this time focusing on Testing and Validating the Model. We’re in the general phase in the Team Data Science Process called “Customer Acceptance“. “Testing” in the general sense is the same in Data Science projects and any other typical software project – it’s ensuring…

1

The Keys to Effective Data Science Projects – Part 8: Operationalize

We’re in part eight on our journey through the series of the Keys to Effective Data Science Projects –“Operationalization” – a term only a marketer could love. It really just means “people using your solution”. And it’s this part of the process that is quite possibly the most complicated, and usually the one done with the…

0

The Keys to Effective Data Science Projects – Part 7: Create and Train the Model

We’re in part seven on our series of the Keys to Effective Data Science Projects.  This is the section that most people think of when they think of “Data Science”. It’s where we take the question, the source data which has been turned into the proper Features (and potentially Labels), and select an algorithm or two…

0

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 you’ve grasped…

0

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…

0

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. This is a primary…

0

The Keys to Effective Data Science Projects – Part 3: Import the 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 this year using the same…

0

The Keys to Effective Data Science Projects – Part 2: The Question

In a previous post I explained where to start in a Data Science Project. I’ve also given you a Project Plan that shows all the steps you need to help your organization with a Data Science objective. The first step in that Project Plan is “Business Understanding”, and the first step in that process is defining the problem…

0

The Keys to an Effective Data Science Project – Part 1: The Team Data Science Process

Processes are great things. They give you a place to start, a roadmap, and a way to explain to your stakeholders (like customers) what you’re going to do and the order you’ll do it. In this series, I’ll explain a few keys to creating a successful Data Science and AI Project. In addition, a process…

0

Data Science: Start at the very Beginning, It’s a very good place to start

I have found that Data Science projects often deal with two types of clients: One of whom understands the Data Science Process and has a good grasp of what it can do, and the other who wants to add a dash of Machine Learning (ML) and/or Artificial Intelligence (AI) on top of Business Intelligence to find…

0