vincelam

A live dashboard tracking hundreds of open-source LLM repositories - updated daily with stars, forks, and growth trends so you can spot what the community is actually building with right now.

A timeline of my fitness journey - key milestones, personal bests, and small experiments across different sports over the years.

How I used AI to design, iterate, and maintain a periodised 20-week training plan for HYROX and a half marathon - from writing the metaprompt to updating it with real data.

A compilation of Singapore's exploding run club scene.

Exploring how single-file HTML tools and AI coding assistants have transformed my workflow - from idea to deployed tool in minutes.

My notes on essential machine learning design patterns from Google Cloud experts, featuring practical insights on ML system architecture and implementation strategies for engineers.

Everyone argues on the definition of an AI agent because it's hard to define *exactly* what an AI agent is.

A comprehensive comparison table of open-source AI Agents frameworks.

There are many open-source tools for hosting open weights LLMs locally for inference, from the command line (CLI) tools to full GUI desktop applications.

Here's a collection of tools that have genuinely enhanced my daily productivity as a knowledge worker and data scientist.

Here's why I recently switched my blog framework from Jekyll to Astro.

If you’ve heard of the term "embeddings” before but don’t quite understand it, this post is for you.

When there is a data science problem to solve, my instincts are to start coding and build something impactful with the latest technologies.

Knowing traditional NLP tasks is useful to understand the capabilities of (Large) Language Models.

Moving to Singapore with zero connections, I faced the challenge of building a professional network from scratch.

Understanding the training process of AI assistants reveals how they evolve from simple language models to sophisticated, useful tools.

Large Language Models (LLMs) are complex probabilistic machines that predict the next word.

I've read 4x as many books this year compared to previous years by implementing these tips.

In this post, I’ll share how I transitioned from mechanical engineering to data science in 2020 while working full-time.

In today’s tough job market, especially in the competitive data science field, writing online and building a personal profile helped me stand out and find freelance work.

Last year, my partner and I made a life-changing decision to uproot our comfortable lives in London and move to Singapore.

I recently signed up to an online writing course.

Keeping up with the latest breakthroughs and industry trends can feel like an endless pursuit, leading to information overload.

Here's why Raycast is a game-changer for productivity and I'll highlight my most frequent use cases and demonstrate how you can significantly improve your workflow.

As someone who regularly uses Large Language Models (LLMs) for personal use and builds apps with LLMs - the choice between self-hosted open weights LLMs and proprietary LLMs is a recurring theme.

Here are my highlights from Jensen Huang's keynote, NVIDIA CEO, hosted by ATxInspire Singapore.

Here are my highlights from H2O.ai's Singapore GenAI Day, a fantastic event showcasing their latest contributions to GenAI.

Here are my thoughts on OpenAI's recent Dev Day announcements.

For this blog post, I'll focus on tabular and time-series data (in the context of machine learning (ML) competitions) since this is the most common data type that data scientists face and has the highest applicability/utility.

In this beginner-friendly post I’ll introduce the concept of anomaly detection, also known as outlier detection, focusing on the popular technique of density estimation.

Here’s an overview of what I’ve been up to and my main takeaways from 24 hours of meetups and conferences on Generative AI, Machine Learning for finance, and Data Engineering.

Thanks for stumbling upon my website.