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Building Your Own ML Model with Pecan: A Walkthrough for Everyone
Building Your Own ML Model with Pecan: A Walkthrough for Everyone

Unlock the power of machine learning in 4 easy steps with Pecan—no PhD required! Perfect for BI analysts and data enthusiasts alike.

Ori Sagi avatar
Written by Ori Sagi
Updated over a week ago

Ever thought building a machine-learning model would be out of reach? Well, think again. Pecan has streamlined the entire process, making it as easy as 1-2-3 (and a 4). Whether you're a BI analyst or someone just starting out in predictive analytics, here’s your easy guide to go from zero to predictive hero!

Step 1: Connect Your Data

Before getting started, make sure you have at least 1,000 rows of data—this is your golden ticket to the ML universe. Connecting your data to Pecan is the first stage, and it's as simple as uploading a CSV file or choosing one of our many integrations. No data preparation is needed!

Check out our deep-dive section on data connection for more information.

Step 2: Choose Your Template

Templates are your best friends here—they give you a ready-made framework so you don't have to start from scratch. Pecan offers a variety of templates tailored for different business needs and industries. Don't be overwhelmed by choices; each template comes with its own set of guidelines to help you choose wisely.
Learn more about selecting the right template here.

Step 3: Fine-Tune Your Predictive Question

Next up is the Editor stage, where you customize your model. It's like tailoring a suit; you want it to fit perfectly. In the Editor, you'll specify the entity you're interested in (e.g., customer, product), set your target variable (what you're trying to predict), and add attributes to give your model more context. And guess what? You can do this with simple spark SQL.
SQL aficionados, this is your playground! Get into the nitty-gritty of the Editor stage here.

Step 4: Train and Evaluate Your Model

Once your predictive question is set, it's time to train your model. Pecan does the heavy lifting for you here. After the training is complete, you'll get a dashboard that shows how your model is performing. It's like your model's report card, but without the dread of parent-teacher meetings. Learn how to interpret your dashboard metrics here.

And voila, you've just built your own machine-learning model! It's that simple.

Ready to take the plunge? With Pecan, you don't need a PhD in Data Science—just a willingness to dive in and let us guide you through the nuts and bolts of predictive analytics.

So, what are you waiting for? Start your 2-week free trial today and join the future of data analytics!

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