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

Day 71 to 81 of #100DaysOfcode

- listen to x-spaces about career resiliencies by recruiters, sr. engineers.
- going through fundamentals of graphql, nodejs, reactjs
- watching podcast of kelesy hightower on being engineer that people values.

#LearnInPublic

Day 45 of learning AI/ML

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

• Representing quantitative data
• Frequency tables & dot plots
• Creating & interpreting histograms
• Stem and leaf plots

#LearnInPublic #AI #ML

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— Ayesha | FlutterMobile App Developer 📱 #FlutterDev #MobileApp #BuildingInPublic #LearnInPublic #ayeshappdev

Day 44 of learning AI/ML

I studied Statistics & Probability
(Khan Academy - Unit 1)

• Identifying marginal vs conditional distributions
• Marginal distributions from two-way tables
• Conditional distributions within categories
• Understanding relationships between variables

#LearnInPublic #AI #ML

Day 43 of learning AI/ML

I studied statistics & Probability
(Khan Academy-Unit 1)

•Venn diagrams for relationships between sets
•Two-way frequency tables
•Two-way relative frequency tables
•Interpreting categorical data
•Identifying trends & associations in categorical data

#LearnInPublic #AI #ML

Day 42 of learning AI/ML

I studied Statistics & Probability
( Khan Academy - Unit 1)

• Individuals & variables
• Categorical variables
• Data visualization: pictograph, bar chart, pie chart
• Measures of center: mean (average), median, mode
• Range & midrange

#LearnInPublic #AI #ML

Day 41 of learning AI/ML

I practiced linear algebra in Python with NumPy

• Vector scaling, addition, subtraction
• Element-wise multiplication
• Matrix × vector operations
• Matrix multiplication
• Determinant calculation
• Eigenvalues computation

#LearnInPublic #AI #ML

GraphQL Roadmap Step by step guide to learn GraphQL in 2026

Today is another Fundamentals clearing day.

so, for that reason, I picked up graphql.

making anki cards, checking out their official websites.

of course, from roadmap.sh/graphql as well.

#learninpublic

Day 40 of learning AI/ML

I studied abstract vector spaces
(3blue1brown)

• What makes something a vector (axioms)
• Functions as vectors
• Linear operators acting on vectors
• Matrices extending to infinite dimensions
• Why abstraction matters in math

#LearnInPublic #AI #ML

thoughtsre | Binghao Ng | Substack My thoughts on applied math, data science, machine learning, innovation and other random musings that come to my mind. Click to read thoughtsre, by Binghao Ng, a Substack publication. Launched 2 years...

Serious curiosity means you don't stop at "I get the idea." You work through the math, write the code, hit the walls, and come out the other side actually understanding it. That's what I write about at thoughtsre.substack.com.

#LearnInPublic

Day 39 of learning AI/ML

I studied eigenvectors & eigenvalues

• Eigenvectors - directions unchanged by a transformation
• Eigenvalues - how much those vectors scale
• Quick trick for computing eigenvalues
• Geometric meaning of eigenvectors

#LearnInPublic #AI #ML

Day 38 of learning AI/ML

I studied linear algebra
Source: 3blue1brown

• Cross product viewed as a linear transformation
• Cramer’s Rule - geometric way to solve linear systems
• Change of basis - vectors in different coordinate systems
• Translating coordinate systems

#LearnInPublic #AI #ML

Day 37 of learning AI/ML

I studied dot & cross products (linear algebra)
Source: 3blue1brown
• Dot product -> measures alignment between vectors
• Same direction -> positive
• Perpendicular -> 0
• Opposite direction -> negative
• Cross product -> vector perpendicular to both

#LearnInPublic #AI #ML

Day 36 of learning AI/ML

I studied linear algebra fundamentals

Key points
•Inverse matrices
•Column space -> all vectors a matrix can produce
•Null space -> vectors mapped to zero
•Linear systems of equations
•Non-square matrices as dimension-changing transformations

#LearnInPublic #AI #ML

Day 35 of learning AI/ML

I studied: Linear transformations in 3D & determinants
source: 3blue1brown

Key points:
•3D transformations using 3×3 matrices
•Matrix multiplication in three dimensions
•Determinant as volume scaling factor
•Determinant sign -> orientation flip

#LearnInPublic #AI #ML

Day 70 of #100DaysOfcode

- reading the blog post of Mitchel Hashimoto's ai adoption journey (mitchellh.com/writing/my-a...)
- then checking out GitHub repo of (agents.md) website.
- came across something really neat algorithm called ( fisher-yates algorithm )

#LearnInPublic

The naked truth about AI-assisted coding The naked truth about AI-assisted coding / In this article, I argue that AI-assisted coding is useful but overhyped. I see real value in speeding up boilerplate and first drafts, but I also see seriou...

Interesting Read.

krasimirtsonev.com/blog/article...

this blog post dive deep into the *Ai Assisted Coding* truthiness.

and honestly i've felt this too in my day jobs and side hustles.

#LearnInPublic

Interesting Read.

mitchellh.com/writing/my-a...

this is about blog of mitchel hashimoto's ( founder of harshicorp) ai journey.

he shares a lot. in this blog

#ai #learninpublic

Today I just decide to checkout the *OpenClaw* project that everyone been talking about.

let see what it's got.

#LearnInPublic

Day 65 to 69 of #100DaysOfcode

- continue reading book about ai engineering.
- reading articles about awesome engineering blogs froom the GitHub repo.
- applying to jobs. and preparing myself for interviews.
- learning basic fundamentals about *cloud* technology.

#LearnInPublic

I was thinking really "lightly" of regex.

but now understand that large portion of the "redos" attack that happens. Are due to regex vulnerability.

learned something really interesting.
#LearnInPublic

owasp.org/www-communit...

Ranked up to 6kyu on Codewars. I've built a habit over time of doing one challenge a day. I've gotten pretty comfortable with 7kyu so I suppose it's time to move up to the next level 💪 #learninpublic #100devs

Getting out and about: An ode to coworking outside Recently I have found that coworking outside of the home has yielded several benefits for my mental health and social needs.

I've been getting out a bit more lately and working with friends in a coffee shop or restaurant. I used to think people were crazy to do it, but now I see the appeal! medium.com/@amccollum.d... #learninpublic #100devs #softwaredevelopment

Day 59 to 64 of #100DaysOfcode

- reading books about ai engineering.

#LearnInPublic

Reading a book is one of the best habit I have.

and these past couple of weeks i'm reading one based on Ai Engineering.

named : Ai Engineering: Build Application with Foundation Models by Chip Huyen

#bookreading #learninpublic #aiengineering

7 weeks of consistent posting. Now adding Web3 to the mix.
If you want to watch someone learn this in real time — mess ups included — follow along.
Let's build something. Together.
#BuildingInPublic #Web3 #LearnInPublic

Tuples Lock Down Array Length and Position Types

Tuples enforce exact array positions and types, fixed length, position-specific safety.

#LearnInPublic #TypeScript #JavaScript