Tag: tutorial
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Hyperparameter Tuning in Machine Learning: When It Matters
Hyperparameter tuning is where data scientists tend to waste the most time. I’ve watched teams spend three weeks tuning a model that had fundamental data problems. They squeezed out a 2% accuracy gain while ignoring that their feature engineering was garbage. In reality, hyperparameter tuning is the last thing you should do, not the first.…
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Model Deployment in Machine Learning: Getting to Production
Model deployment is where most ML projects die. I’ve seen data scientists build brilliant models that never leave their Jupyter notebooks. The model works perfectly in development, it just never makes it to production. A model that sits in a notebook is worth exactly zero dollars. Deployment is what turns your ML work into business…
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Regression Models: When You Need to Predict Actual Numbers
Learn when to use regression models instead of classification. Build customer lifetime value predictions using Linear Regression, Ridge, and Random Forest. Understand MAE, RMSE, and R² metrics with practical Python code.
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ML Fundamentals: Stop Overthinking, Start Building
Learn machine learning fundamentals by building a spam classifier in 30 minutes. Same techniques apply to customer churn and employee attrition prediction. No PhD required—just Python and practical code.
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Classification Models: Pick the Right Tool
Compare four classification algorithms on the same churn dataset. Learn when to use Logistic Regression, Decision Trees, Random Forest, or XGBoost. Understand the performance vs interpretability tradeoff and make principled choices based on business context.
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Data Prep: Where ML Projects Actually Live or Die
Master the 80% of ML work that happens before modeling. Handle missing values, scale features, avoid data leakage, and build proper train/test splits. If your model performs terribly, it’s probably your data prep.
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Getting Data Into PyTorch Tensors
Master PyTorch tensor data loading without the frustration. Learn practical techniques for converting NumPy arrays, lists, and datasets into PyTorch tensors efficiently.
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Getting Started with PyTorch
So you want to get into machine learning and everyone keeps talking about PyTorch? Good choice! PyTorch is basically the cool kid on the ML block right now, and for good reason – it’s way more approachable than you might think. Pytorch doesn’t force you to think like a computer. You can build and tweak…
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Your First 30 Days with Snowflake
Step-by-step guide to learning Snowflake in 30 days. From account setup to advanced features, with SQL examples, common mistakes to avoid, and practical exercises.
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Top 5 New Features in Tableau 2022.1
Tableau 2022.1 brings relationship improvements, Einstein Discovery integration, dynamic zone visibility, and better web authoring. Here’s what actually matters and how to use the new features.
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Tableau vs. Tableau CRM: What’s the Difference?
Confused about Tableau vs. Tableau CRM? Here’s a practical breakdown of the differences, when to use each one, and why Salesforce’s naming makes everything more complicated than it needs to be.
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Free Data Science Software
In the data science world, some of the best stuff is free. I’ve already posted about free books and some of the better videos on YouTube, so now let’s put together a list of software tools. Some of these are limited versions of commercial software. Others, like R, are Open Source packages that have become…
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Educational Videos on Data Science
Here’s a list of some of the better videos I’ve stumbled across over the past couple of years. They range from forward-looking glimpses into the future, to software tutorials. I’d love to grow this list, so if you have a favorite video you don’t see listed here please add it in the comments section below.Note:…