Day 59 of learning AI/ML

I studied Probability
@khanacademy Unit 7

• Theoretical vs experimental probability
• Making predictions using probability
• Simulations & randomness
• Using random digits/numbers for experiments
• Statistical significance of results

#LearnInPublic #AI #ML

Day 58 of learning AI/ML

I studied Probability
@khanacademy - Unit 7

• Union & intersection of sets
• Difference (relative complement)
• Universal set & complement
• Subset, strict subset, superset
• Combining set operations

#LearnInPublic #AI #ML

We have a neighborhood store that uses the Wix store features, so helping set up inventory, a loyalty program, and a new POS system using Wix has been a great experience. #LearnInPublic #Volunteering

Day 57 of learning AI/ML

I studied Probability
@khanacademy Unit 7

• Intro to theoretical probability
• Sample spaces & subsets
• Coin flips & dice probabilities
• Simple events
• Intuition behind probability
• Monty Hall problem

#LearnInPublic #AI #ML

Software Engineering Splits in Three "AI-assisted coding changes the game for enterprises by shifting the bottleneck from coding to judgment, impacting software builds and roles."

This article give me insights on how the current software field is taking shape. and how i can mend around it.

from Matteo Collina 's "Adventures In Nodeland".
#learninpublic

Software Engineering Splits in Three adventures.nodeland.dev/archive/soft...

Day 92 of #100DaysOfcode

- worked on my project.

#LearnInPublic

Day 56 of learning AI/ML

I studied Statistics
@khanacademy Unit 6

• Observational studies vs experiments
• Identifying appropriate study types
• Intro to experiment design
• Matched pairs design
• Principles of experiments

#LearnInPublic #AI #ML

It's image of the problem that solved. problem statemetn : Implment alogrithm to determine if a string has all unique character. I first used brute force approach, like using nested loops so my time complexy went n squuare. then i use js SET() method so my time complexity went O(n)

Today I worked on solving a specific array coding problem from the 'Cracking the coding interview' book

#LearnInPublic

Day 55 of learning AI/ML

What I studied Statistics
@khanacademy Unit 6

• Statistical vs non-statistical questions
• Population vs sample
• Bias in surveys & undercoverage
• Correlation ≠ causation
• Random sampling & fair selection methods

#LearnInPublic #AI #ML

Day 91 of #100DaysOfcode

- work on my side project. setup basic backend. and work on how i'll design the website ( backend) what features to add.

#LearnInPublic

Day 90 of #100DaysOfcode

- nodejs anki reading and prepared for interview.
- checking out opentelemtry. and how it is used in nodejs backend applications.

#LearnInPublic #nodejs #observability #opentelemetry

Day 54 of learning AI/ML

I studied Statistics & Probability
(@khanacademy - Unit 5)

• Squared error & why regression minimizes it
• Regression line examples
• Calculating R²
• Covariance & its link to regression

#LearnInPublic #AI #ML

Making a Stardew Valley birthday game for my wife My wife and I both love Stardew Valley. I’m not the pro that she is at the game, but I’ve created a pretty cool farm with some cows and…

Wrote a blog post today on how I made the Stardew Valley birthday game for my wife's birthday. It was a very fun project, something I looked forward to opening up each morning leading up to the final version. medium.com/@amccollum.d... #learninpublic

Day 89 of #100DaysOfcode

- nodejs anki reading and prepared for interview.
- work on my personal project, adding few issues that need to be taken care off.

#LearnInPublic #nodejs

Day 53 of learning AI/ML

I studied Statistics & Probability

• Residuals & least squares regression
• Regression line equation
• Interpreting slope & intercept
• Residual plots & model fit
• R² (coefficient of determination)
• Impact of outliers on regression

#LearnInPublic #AI #ML

#Django #Python #LearnInPublic #LLM

Day 88 of #100DaysOfcode

- checkout various engineering blogs

#LearnInPublic

GitHub - thedhruvish/build-own-mail-server: A simple, lightweight, and self-hosted mail server built with Node.js and TypeScript. This project provides both an SMTP server to receive emails and a web-... A simple, lightweight, and self-hosted mail server built with Node.js and TypeScript. This project provides both an SMTP server to receive emails and a web-based dashboard to view, search, and send...

I’m developing a mail server.

Feel free to check it out on GitHub : github.com/thedhruvish/...

I have knowledge of DNS configurations such as MX and TXT records, as well as how emails are sent.

#nodejs #backend #backend #learnInPublic #gmail #mail #aws #nodejsdeveloper #nodejs #typescript

Day 52 of learning AI/ML

I studied Statistics & Probability
@khanacademy Unit 5

• Scatter plots & relationships
• Direction, strength & linearity
• Positive/negative correlation
• Outliers & clusters
• Correlation coefficient
• Intro to trend lines & line of best fit

#LearnInPublic #AI #ML

Day 85, 86, 87 of #100DaysOfcode

- watching and understanding the worker threads and child process and streams in nodejs

#LearnInPublic #nodejs

Day 51 of learning AI/ML

I studied Statistics & Probability
@khanacademy - Unit 4

• Understanding normal distribution intuitively
• Empirical rule
• Z-score practice & interpretation
• Using standard normal table (below/above/between)
• Finding z-score from percentiles

#LearnInPublic #AI #ML

Day 50 of learning AI/ML

I studied Statistics & Probability

• Percentiles & cumulative frequency graphs
• Z-scores & normal distribution problems
• Comparing data using z-scores
• Effects of linear transformations
• Density curves & skew (mean vs median)

#LearnInPublic #AI #ML

Day 84 of #100DaysOfcode

- checking redis concepts.
- checking out open source observability tools.

#LearnInPublic #nodejs #redis

Day 49 of learning AI/ML

I studied Statistics & Probability

• Why variance uses (n−1) -> unbiased estimate
• Sample vs population variance
• Box plots (create, read, interpret)
• Identifying outliers (1.5×IQR rule)
• Range, midrange & mean absolute deviation

#LearnInPublic #AI #ML

Day 83 of #100DaysOfcode

- optimized my linkedin profile
- did freecodecamp daily challenges.
- read nodejs architectural pattenrs ( monolith vs modular )
- read redis interview questions. and tomorrow planning to deep dive into it in nodejs context.

#LearnInPublic #nodejs #redis

I've played enough of the game to write some dialog that kinda resembles the characters. Should be a fun moment for her. (2/2) #100devs #LearnInPublic

Day 48 of learning AI/ML

I studied Statistics & Probability
(Khan Academy - Unit 3)

• Interquartile range & range
• Variance & standard deviation
• Understanding spread of data
• Population vs sample variance/std
• Mean & std vs median & IQR

#LearnInPublic #AI #ML

Day 47 of learning AI/ML

I studied Statistics & Probability
(@khanacademy -Unit 3)
• Calculating mean, median, mode
• Effects of outliers on mean & median
• Impact of shifting, adding, removing data
• Mean as the balancing point
• Solving missing-value puzzles

#LearnInPublic #AI #ML

Day 82 of #100DaysOfcode

- focusing on few open source projects. experimenting with them.
- and reading codebases to understand higher concepts of nodejs, like streams, buffers, workerthreads.

#LearnInPublic #nodejs

Day 46 of learning AI/ML

I studied Statistics & Probability
(@khanacademy - Unit 2)

• Shapes of distributions
• Identifying clusters, gaps & peaks
• Comparing distributions with dot plots, histograms & box plots
• Comparing center and spread of datasets

#LearnInPublic #AI #ML