DEV Community: Daniel Githinji

Data science books found interesting to read.

Daniel Githinji — Wed, 12 Aug 2026 01:42:17 +0000

recommended books
I mean, I can't really recommend books to you since I don't really know who you are. But these are books I really adore. I almost exclusively read nonfiction, so there are not any fiction recommendations.

Science Popularizations
T-Rex and the Crater of Doom - Walter Alvarez
A compelling story that clearly lays out the combination of hard work and total luck that leads to big discoveries in science. So good!

The Immortal Life of Henrietta Lacks - Rebecca Skloot
Dives deep into ethics, race, poverty, medicine and medical research. Reads like investigative journalism, but more thoughtful. For months after reading this book, it was my go-to for conversations - I just had to tell everyone the story.

The Unwanted Sound of Everything We Want - Garret Keizer
This is a hard book to describe because it is so sprawling but also so personal. My favorite quote from the book captures the theme well: "The essential difference between music and noise is neither acoustic nor aesthetic but ethical."

Algorithms to Live By: The Computer Science of Human Decisions - Brian Christian, Tom Griffiths
This is the rare popularization that is accessible and interesting to a broad audience, but even folks I have talked to that study math or computer science learned interesting things from it.

Sun in a Bottle: The Strange History of Fusion and the Science of Wishful Thinking - Charles Seife
Learning about the history of fusion research was neat, but my favorite aspect of the book was seeing how many different ways scientists have failed at cold fusion. I liked the books above better, but this is a good runner up.

Data Science
There are lots of good textbooks on specific problems related to data science, but these are my favorites because the cover the big, complicated, messy world in accessible ways. They are all accessible

Confident Data Skills: Master the Fundamentals of Working with Data and Supercharge Your Career - Kirill Eremenko
I can only recommend chapters 1-5, but those are the best description I have found of what I do as a data scientist all day. Easy read - no math and lots of emphasis on understanding problems, soft skills and process.

The Visual Display of Quantitative Information - Edward R. Tufte
This is the classic book in data visualization. Because the recommendations have been so widely adopted, it now reads as less revolutionary than it was. I still recommend borrowing a copy and flipping through it.

Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy - Cathy O'Neil
I can't say I agree with everything in this book, but I have read quite a few critiques of how data / automation / AI / algorithms / etc. are harming society, and this is the most thoughtful and timely.

Textbooks
Pattern Classification (2nd Edition) - Richard O. Duda, Peter E. Hart and D. G. Stork
You want to understand machine learning? There are lots of books right now about how to do machine learning, but this 20 year old book lays out the basics in a way that is easy to understand. The appendix has the most clear and straightforward overview of the linear algebra and probability that you need.

Understanding Digital Signal Processing - Richard G. Lyons
This is a practical guide to actually implementing digital signal processing. Covers tons of important topics that aren't taught in school, and the extremely practical approach really worked for me. I read the 2nd edition, but there is a third now.

Nonlinear Dynamics and Chaos - Steven H. Strogatz
I loved this math textbook. I wish every math text could be like this.

Div, Grad, Curl, and All That: An Informal Text on Vector Calculus - H. M. Schey
Extremely informal, but this really helped me make sense of vector calculus. It should be paired with a proper textbook, but if you are struggling with

Books that changed my life, but I read them as a teenager
Chaos: Making a New Science - James Gleick
I read this book in undergrad, and it was thrilling to learn about the background of the things I was studying. It helped me seperate the concepts of uncertainty and randomness, and I think often of the 1-2-3 punch of the Heisenberg's uncertainty principle, Gödel's incompleteness theorems, and chaos in deterministic systems. I think in some ways data science is as much a response to those discoveries of the 20th century as they are to the rise in computers.

Nonzero: The Logic of Human Destiny - Robert Wright
Almost all interactions are not zero sum. Some of them are mutually beneficial, and others are mutually harmful. I think about this every day, despite reading this book roughly 20 years ago. I feel really badly for (and often am afraid of) people who see the world as zero sum.

Nature doesn't attack in silos. Why should our defenses?

Daniel Githinji — Sat, 08 Aug 2026 14:30:43 +0000

One hazard is a disaster. Two hazards at once is a catastrophe.

Enter TINA-X. 🛡️ We don't just track the weather; we track the collapse. Using advanced symbolic AI, we map the hidden connections between earthquakes, typhoons, power grids, and supply chains to predict cascading failures before they happen.
See the network. Spot the vulnerability. Protect the core. ⚡🟠🔵

Front-end challenge Submission

Daniel Githinji — Sun, 02 Aug 2026 14:14:45 +0000

This is a submission for Frontend Challenge - Comfort Food Edition, Perfect Landing

What I Built

Nairobi runs on a chaotic, vibrant energy. Professionals working from boutique hotels in Westlands or Kilimani need food that matches that energy: fast, healthy, and unapologetically local.
The stereotype of "boring village food" is dead. I built Pamoja Plate—a digital love letter to Kenya's culinary diversity. It’s not just a food delivery site; it’s an interactive journey through the country's regions, all unified on a single plate.

The Concept:

Instead of a standard menu grid, I built an interactive "Unity Plate" experience. Using a custom accessible accordion pattern, users can explore six distinct regional dishes—from the Omena of Lake Victoria (Nyanza) and Wali wa Nazi of the Coast to Nyama Choma of the Rift Valley and Ugali from the Central highlands. When a user clicks a dish, a CSS-art platter visually highlights that specific region's contribution, creating a dynamic, educational, and mouth-watering UX.

Demo

MVP link

Journey

I wanted to capture a highly specific, localized persona rather than relying on a generic template. The challenge was combining professional investor-ready design with authentic local slang and vibe.
What I Learned:

Responsive Image Mapping is Hard: Attempting to overlay clickable hotspots (blobs) precisely over a photograph using CSS percentages is highly susceptible to breaking when aspect ratios change.
Accessible Alternatives Win: Moving to a "Pill Navigation" system not only solved the responsive layout issues but also vastly improved accessibility. Users no longer have to guess where to click; the options are explicit.
Single Source of Truth: Using a single piece of React state (activeLayer) to drive both the pill button highlighting and the accordion dropdown state is an elegant way to synchronize disconnected UI elements.

What I'm Proud Of:
The transition from a frustrating, brittle interaction (the image hotspots) to a clean, highly accessible pill navigation system. The interface now feels synchronized and responsive.

I'm particularly proud of the pure CSS art component in the Hero section— rendered entirely using CSS and HTML div primitives, complete with a custom gradient for the steam animation keyframes. I also focused heavily on accessibility, ensuring semantic HTML, high contrast text ratios, and aria-pressed states on the interactive guarantee toggle.
Next up, I plan to integrate the WhatsApp Business API directly into the ordering flow for the "25-Minute Flex" rider logistics!

Members

sqware

Building What Is Missing.

Daniel Githinji — Sun, 19 Apr 2026 16:48:21 +0000

I just hit a wall that most developers ignore until it is too late.

I wanted to build an integration on Move, Scrypto and Cairo.

I looked for real ecosystems I could plug into on devdocs.io. They were not there. Not usable. Not accessible. Not built for someone who wants to ship fast. So I made a decision. I will build the ecosystem myself. Here is the shift most people miss. Developers wait for perfect infrastructure. Builders create it. I stopped searching and started defining what I needed.

→ A clean developer onboarding flow

→ Real documentation that does not waste time

→ Tooling that works out of the box

→ A small but active community

→ Clear use cases that people can build on

I am not trying to compete with every chain. I am solving one problem. Make Move, Scrypto and Cairo usable for builders who want to move fast. I started mapping the gaps. I listed every friction point I hit in the first 48 hours. Then I turned each one into a feature. That became the foundation of the ecosystem. Most people talk about adoption. Adoption comes after usability. If developers cannot build, nothing else matters. So I am building the thing I wish existed last week. If you are a developer who felt the same pain, you already know why this matters.

The Unspoken Truths of Dev Work: How I Wrestled My Data Science Project onto GitHub (and learned some secrets)

Daniel Githinji — Tue, 14 Oct 2025 04:56:53 +0000

Every developer knows the drill: write code, solve problem, push to GitHub. Simple, right? Not always. As I tackled the Week 3 homework for the Data Talks Club scholarship—focused on lead scoring with a classic ML workflow—my journey from Google Colab to a clean GitHub commit turned into a mini-saga of real-world dev frictions.

This isn't just about getting the right answers (though I got those too, for Q1-Q6 on mutual information, feature elimination, and regularization). It's about how the actual process of deployment and version control can sometimes teach you more than the algorithms themselves.

The Setup: Colab Comfort & GitHub Ambition
My environment of choice was Google Colab—fast, free, and great for quick iterations on ML tasks. My goal: complete the homework, export the notebook, and push it to my GitHub repo (dgithinjibit/dataTalksClubWeek3). Sounds straightforward for a developer building a platform like SyncSenta, right?

The plan was clear:

Code the ML solution in Colab.

git clone the empty repo in Colab.

git add, git commit, git push.

Friction Point #1: The Phantom Branch - src refspec main does not match any
After getting the initial code down, I hit my first snag. After running git init (which you generally don't do when cloning an existing repo), and then attempting to push, I got the infamous:

error: src refspec main does not match any
error: failed to push some refs to 'https://github.com/dgithinjibit/dataTalksClubWeek3.git'
The Lesson: This error is Git's polite way of saying, "Hey, you're trying to push a main branch, but your local repository doesn't actually have a main branch with any commits yet!" A branch only truly exists in Git after its first commit.

The Fix: A git clone of the (empty) remote repo, followed by an mv of my notebook into that cloned folder, then a proper git add and the crucial first git commit. This establishes the local main branch. Always commit before you push, especially for the first time on a new branch.

Friction Point #2: The Elusive File - mv: cannot stat '../datatalksweek3.ipynb': No such file or directory
Even after getting the Git commands right, the Colab file system threw a curveball. My mv command to move the notebook into the repo folder failed:

mv: cannot stat '../datatalksweek3.ipynb': No such file or directory
The Lesson: Colab notebooks, especially those opened from or saved to Google Drive, aren't always sitting in the /content/ directory. You need to explicitly mount your Google Drive if that's where the file resides. Otherwise, the Colab runtime can't see it.

The Fix: Mounting Google Drive (from google.colab import drive; drive.mount(...)) and using the absolute path (/content/drive/MyDrive/Colab Notebooks/datatalksweek3.ipynb) was the solution. It's a reminder that even in "cloud" environments, file paths are king.

Friction Point #3: The Secret Sneak - GitHub Push Protection Strikes!
Just when I thought I was home free, GitHub's automated security stepped in:

remote: error: GH013: Repository rule violations found for refs/heads/main.
remote: - GITHUB PUSH PROTECTION
remote: —————————————————————————————————————————
remote: - Push cannot contain secrets
remote: —— GitHub Personal Access Token ——————————————————————
remote: locations: datatalksweek3.ipynb:1
The Lesson: My Personal Access Token (PAT) — which I used to authenticate Git operations in Colab — was inadvertently saved within the notebook's output cells. GitHub's Push Protection caught it. This is critical. Never commit secrets to a public repository. It's a fundamental security principle.

The Fix (The "Clean Code" Way):

Downloaded the notebook locally. This was the fastest way to get full control.

Manually edited the .ipynb file in VS Code, deleting the entire cell where the PAT was used and, crucially, where its output was stored. No git filter-repo gymnastics needed.

Used git reset HEAD^ --hard to undo the previous bad commit locally.

git add, git commit the clean notebook.

git push origin main (no force needed this time, as the remote was still empty).

The Takeaway: Beyond the Algorithm
This wasn't just homework; it was a crash course in the practicalities of a developer's workflow. From understanding how Git actually builds its history, to navigating cloud file systems, to prioritizing security and clean commit practices—these "frictions" are where the real learning happens.

As I continue building SyncSenta and pushing the boundaries of AI in education, these are the lessons that build resilient systems and a robust development pipeline. It's not just about writing code; it's about owning the entire stack and adapting to every challenge that comes your way.

What are your "tedious" dev lessons that turned into critical skills? Share in the comments!

Conjuring Cards from Code: Building an AI Magic: The Gathering Generator with Gemini

Daniel Githinji — Sat, 09 Aug 2025 15:41:56 +0000

This post is my submission for DEV Education Track: Build Apps with Google AI Studio.

What I Built

Demo

Here's a look at the final application in action. You can try it yourself here:
https://aistudio.google.com/app/prompts?state=%7B%22ids%22:%5B%221DompvESeXnO86aBQU5HLunUXAHLIs0ZY%22%5D,%22action%22:%22open%22,%22userId%22:%22115709936703047334177%22,%22resourceKeys%22:%7B%7D%7D&usp=sharing
The user journey is simple: just type a creative idea into the prompt box and hit "Generate Card".

After a few seconds, the AI delivers a brand-new card, complete with stunning artwork, and a separate section that reveals the rich lore behind your creation.

My Experience

10 Things to Keep Private for a Spotless Reputation

Daniel Githinji — Fri, 13 Jun 2025 11:19:58 +0000

In an era where oversharing is the norm, maintaining a pristine reputation requires discretion. Let's dive into these points and analyze why they matter.

Long-term Goals (Until You’ve Taken Real Action)
Sharing your ambitious goals can be exciting, but it can also backfire. Publicly announcing goals can trick your brain into feeling accomplished, making you less likely to follow through. Keep your plans quiet and let your actions speak louder than your words.
Intimate Details About Your Love Life
Oversharing about your relationship can make it seem unstable, even if it isn't. Respect your partner's privacy and dignity by keeping intimate details to yourself.
Acts of Generosity
Helping others is commendable, but flaunting your good deeds can make you seem self-congratulatory. True generosity doesn't seek an audience; it comes from the heart.
Family’s Flaws and Dysfunctions
Airing your family's dirty laundry can create unease and damage your perception. Keep family issues private, especially in professional settings.
Financial Situation (in Detail)
Whether you're wealthy or struggling, your financial situation is personal. Bragging or complaining about money can make you seem arrogant or unstable.
Past Mistakes (especially if they’re still raw)
Sharing unprocessed past mistakes can lead to judgment and define you by your worst moments. Wait until you've healed and gained wisdom before sharing your stories.
Gossip Others Have Told You in Confidence
Keeping secrets shows your integrity. Don't leak confidential information, as it can quickly tarnish your credibility.
Your Insecurities (with the wrong people)
While it's good to talk about insecurities with trusted friends, constantly advertising self-doubt can question your competence. Save that vulnerability for those who can support you.
Spiritual or Political Beliefs (in Polarizing Environments)
Your beliefs are personal and complex. Shouting them in every room can alienate others. Know when to listen rather than preach, and maintain your reputation in diverse settings.
Your Next Move
Keeping your plans close to your chest until it’s time to act can prevent resistance and drama. Act quietly and decisively, without seeking validation.

Final Thoughts

In a world that encourages oversharing, knowing what to keep private is crucial for maintaining your reputation. Your inner life is sacred, and the most powerful people are those who discern what to reveal and what to protect. Think twice before sharing, and remember that sometimes, silence is stronger than words.

This analysis underscores the importance of discretion in maintaining a strong reputation. By keeping certain aspects of your life private, you can ensure that your public image remains intact and respected.