Aaron 🥞I revamped my profile page using just HTML and TailwindCSS (with like 6 lines of JavaScript), removing thousands of lines of CSS and SASS that I didn't quite understand from my old HTML template. I wrote about the process: https://kyaaron.github.io/aaron-blog/#/post/2026-05-18-revamping-my-profile-page-with-gemini-and-cursor #LearnInPublic #100devs #ai #coding
I created my first web API, which was a funny and fun project. https://kyaaron.github.io/aaron-blog/#/post/2026-05-07-creating-my-first-api #100devs #LearnInPublic #WebAPI #coding
LogicLuminaryBill🌟 Sunday, April 26, 2026 🌟
Progress Update
Day 115 of Year 3 | Day 846 overall since Jan 1, 2024
📚 Daily Reading
✅ freeCodeCamp News — 1 article
✅ Daily.dev — 1 article
💻 Learning Focus
• freeCodeCamp: Python ~ Mastering String Slicing 🔪✨
Leveling up with string slicing—because the more you refine your skills, the cleaner your code becomes.
#Python #StringSlicing #CodingPractice #LearnInPublic #DevJourney #TechGrowth #CodeLife #Consistency
ChitraDay 87 of learning AI/ML
I studied Inference for regression slope
• Inference about slope (linear regression)
• Conditions for valid inference
• Confidence interval for slope
• t-statistic for slope
• Using p-value to conclude
Day 86 of learning AI/ML
I studied Chi-square tests (tables & association)
• Frequency & contingency tables
• Chi-square test for homogeneity
• Chi-square test for independence
• Testing relationships between variables
Day 85 of learning AI/ML
I studied Chi-square tests (categorical data)
• Inference for categorical data
• Chi-square distribution (intro)
• Goodness-of-fit test
• Chi-square statistic
• Interpreting results
Day 84 of learning AI/ML
I studied Comparing means
• Statistical significance (real example)
• Difference of sample means distribution
• Confidence interval for difference of means
• Hypothesis test for difference of means
Day 83 of learning AI/ML
I studied Comparing population proportions
• Comparing two population proportions
• Hypothesis testing for proportions
• Interpreting statistical significance
• Drawing conclusions from experiments
Day 82 of learning AI/ML
I studied Hypothesis testing (summary)
• Hypothesis testing & p-values
• One-tailed vs two-tailed tests
• z vs t statistics
• Small vs large sample tests
• Proportion hypothesis testing
Day 81 of learning AI/ML
I studied Hypothesis testing for a mean
• Writing hypotheses (mean)
• Conditions for t-test
• When to use z vs t
• Calculating t-statistic
• Finding & comparing p-values
• Making conclusions from test