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LLM Monitoring and Observability: Hands-on with Langfuse
In this tutorial, we will start by learning the basics of LLM monitoring and observability. Then, we will explore the open-source ecosystem, culminating our discussion on Langfuse. Finally, we will implement monitoring and observability of a Python based LLM application using Langfuse.
What is Monit...
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Why Your Prompts Don’t Belong in Git
When I was building and shipping my first Generative AI product, I did what most of us do. I hard-coded the prompts. It worked until it didn’t. Every time I wanted to tweak the tone, improve the wording, or fix a hallucination, it meant pushing code and re-deploying the service.
This made fast itera...
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Positional Embeddings in Transformers: A Math Guide to RoPE & ALiBi
To solve this, positional embeddings were introduced. These are vectors that provide the model with explicit information about the position of each token in the sequence. By combining token embeddings with positional embeddings, the model can learn to leverage word order and understand the contextua...
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Using Google’s LangExtract and Gemma for Structured Data Extraction
Important details (e.g., coverage limits and obligations in insurance policies) are buried in dense, unstructured text that is challenging for the average person to sift through and digest.
Large language models (LLMs), already known for their versatility, serve as powerful tools to cut through this...
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The Math You Need to Pan and Tilt 360° Images
0. Introduction
You’re certainly already familiar with spherical or 360 images. They’re used in Google Street View or in virtual house tours to give you an immersive feeling by letting you look around in any direction.
Since such images lie on the unit sphere, storing them in memory as flat images m...
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How to Develop Powerful Internal LLM Benchmarks
However, these benchmarks have an inherent flaw: The companies releasing new front-end models are strongly incentivized to optimize their models for such performance on these benchmarks. The reason is that these well-known benchmarks are essentially what set the standard for what’s considered a new ...
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Plato’s Cave and the Shadows of Data
I hope it entertains you—and sparks a few reflections along the way.
In Plato’s Republic, prisoners sit chained inside a cave. There’s a fire burning behind them and, on the wall before them shadows flicker. These shadows are all the prisoners ever see. They mistake them for reality itself, unaware ...
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Time Series Forecasting Made Simple (Part 4.1): Understanding Stationarity in a Time Series
But these forecasting models require the data to be stationary. So first, we will discuss what stationarity in a time series actually is, why it is required, and how it is achieved.
Perhaps most of you have already read a lot about stationarity in a time series through blogs, books, etc., as there a...
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A Brief History of GPT Through Papers
0) Prologue: The Turing test
In October 1950, Alan Turing proposed a test. Was it possible to have a conversation with a machine and not be able to tell it apart from a human. He called this “the imitation game”. It was introduced in the paper “Computing Machinery and Intelligence”. He was intending...
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Everything I Studied to Become a Machine Learning Engineer (No CS Background)
There were many courses, books and resources I used along the way that helped me, but being honest, many of them I wouldn’t have taken in hindsight.
So, I want to review all the things I studied to land a job in machine learning, and then I will tell you which areas were actually worth it and which ...
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Get AI-Ready: How to Prepare for a World of Agentic AI as Tech Professionals
One question I think about a lot is: If intelligence becomes a utility, what becomes of expertise?
Sure, we’ve automated before. But this time is different. The rise of concepts like Agentic AI (systems with the autonomy to plan, infer, and act) asks us to talk about what this means for the people c...
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Air for Tomorrow: Why Openness in Air Quality Research and Implementation Matters for Global Equity
The principle of Open Source can be a solution. Instead of keeping critical information on air quality data and methods locked behind paywalls, with restrictive access to proprietary algorithms and tools, siloed air quality databases, an open approach is transforming how we research, understand, and...
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Stepwise Selection Made Simple: Improve Your Regression Models in Python
To get the most out of this tutorial, you should already have a solid understanding of how linear regression works and the assumptions behind it. You should also be aware that, in practice, multicollinearity is addressed using the Variance Inflation Factor (VIF). In addition, you need to understand ...
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Graph Coloring for Data Science: A Comprehensive Guide
Note: All figures and formulas in the following sections have been created by the author of this article.
A Theoretical Puzzle
To solve Rita’s problem, let us begin by visualizing the flower petals as a cyclical graph consisting of 6 nodes connected by edges as shown in Figure 1:
Figure 2 shows some...
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A Visual Guide to Tuning Decision-Tree Hyperparameters
Introduction
Based on these two factors, I’ve decided to do an exploration of how different decision tree hyperparameters affect both the performance of the tree (measured by factors such as MAE, RMSE, and R²) and visually how it looks (to see factors such as depth, node/leaf counts, and overall str...
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Implementing the Hangman Game in Python
In this article, we will go through the Hangman Game by implementing it in Python. This is a beginner-friendly project where we will learn the basics of the Python language, such as defining variables, commonly used functions, loops, and conditional statements.
Understanding the Project
First, we wi...
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How to quickly set up a local Spark development environment?
How to quickly set up a local Spark development environment?
- 1. Introduction
- 2. Setup
- 3. Use VSCode devcontainers to set up Spark environment
- 4. Conclusion
- 5. Read these
1. Introduction
Setting up Spark locally is not easy! Especially if you are simultaneously trying to learn Spark. If you...
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5 Things in Data Engineering That Still Hold True After 10 Years
5 Things in Data Engineering That Still Hold True After 10 Years
Why core challenges in data engineering resist the test of time
Hi, fellow future and current Data Leaders; Ben here 👋
When I first started in the data world back in 2015, Hadoop was everywhere. Hortonworks, Cloudera, MapR, all promisi...
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What Separates Good From Great Data Teams
What Separates Good From Great Data Teams
A guide to shifting from outputs to outcomes in your data career
Hi, fellow future and current Data Leaders; Ben here 👋
I’ve had the chance to work with dozens of data teams, each at different stages and with very different infrastructure setups. Sometimes I...
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Review: Building a Real Time Data Warehouse
Review: Building a Real Time Data Warehouse
Many data engineers coming from traditional batch processing frameworks have questions about real time data processing systems, like
“What kind of data model did you implement, for real-time processing?”
“trying to figure out how people build real-time dat...
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