🚀 Machine Learning in Excel?. formulaML is my attempt to bring Machine Learning where people feel most confortable with and where their data already resides - Spreadsheets and using what they already know = formulas. 📊 No Python. No IDE. Just Excel formulas.

Since Python 3.8, there's a handy operator that solves a common pattern:.📌 Assigning a value inside an expression without repeating yourself. It’s called the walrus operator (:=), and although it’s powerful, many developers still don’t fully use it.

🔍 Check out this code:. data = [10, 20, 0, 30, 0, 40]. for x in data:. if (val := x):. print(f"Processing {val}"). 📊 What does this code do?.

Make sure to try Kiro now, it is free, and it's using top tier models with very good limits on usage, so take advantage of it while in Preview!.

I love Kiro mainly for its Specs feature. Unlike Cursor, where I kept switching between tasks and using ChatGPT to understand the bigger picture, Kiro simplifies planning and task implementation.

Now, it is the task list that will be actually executed. Above each task list, you'll see a clickable "Start Task" text. This will launch Claude to actually start writing the code.

This applies to the design and task list. You can refine them anytime or revisit the requirements if needed. Claude reviews your codebase to align requirements, design, and tasks.

Its best feature is the Specs definition. It is a three-part plan:. 1️⃣ Requirements.2️⃣ Design.3️⃣ Tasks. This acts as a normal chat between you and Claude, explaining what you want, how you want it, and success criteria.

It exclusively uses Claude Sonnet 4.0 and 3.7, which is sort of expected given that Amazon has a good stake in Anthropic, and I believe there is some sort of close collaboration.

I have been testing Kiro for a couple of days, and I have to say that it is great!. Kiro is a new AI IDE by AWS, and it is free to try with some good limits on usage.

Bottom line: You don’t need to love statistics. You just need to know enough to make smart calls. Which of these tools do you use the most?.

6. ROC Curves & AUC. Every decision involves trade-offs. ROC curves show what happens when you shift your standards. Example: Comparing two models for loan approvals and balancing false positives against true positives.

5. Confusion Matrix, Precision & Recall. “Accuracy” alone is misleading. Precision and recall show where your model truly stands. Example: Evaluating medical tests where a missed diagnosis matters more than accuracy alone.

4. Linear & Logistic Regression. Basic doesn’t mean boring. These are the bread-and-butter tools that let you predict what’s next. Also, they are my go-to tools for descriptive analytics. Example: Predicting house prices or who’s likely to unsubscribe.

3. Confidence Intervals. One number won’t tell the full story. Confidence intervals give you a range to trust—not guess. Example: Estimating how many users will actually convert, within a realistic range.

2. Hypothesis Testing & p-values. Is your result legit or just luck? Hypothesis tests give clarity. Understand p-values or risk chasing ghosts. Example: Checking if that new website tweak actually boosts sales.

1. Bayesian Inference. Stop ignoring your gut feeling. Bayesian methods combine your prior beliefs with new data. Essential when situations keep changing. Example: Updating your fraud model as new scams pop up.

Most people think statistics is about complicated math. It’s not. It’s about making smarter decisions with data—and if you’re not comfortable with these 6 tools, you’re flying blind.

How about if other Cursor users share their usage graph??? Post it in the comments and let us know about your setup!.

I believe there are many dimensions to this and there is not a simple answer. i.e. (high acceptance rate != low programming experience) since some people might be using these tools better than others. But who knows.

and if your acceptance rate is low:. - Do you have a lot of experience in coding?.- Do you think the generated code is low quality?.- Haven't you used cursor rule or MCPs to provide better answers?.