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Get ready to embark on an exciting journey into the realm of AI and discover how machines can learn and make intelligent decisions. Our blog articles are crafted with simplicity and clarity in mind, making complex machine learning concepts easy to understand for everyone. Whether you’re a beginner or an experienced practitioner, we’ve got you covered with informative and insightful content. Explore the fascinating world of algorithms, models, and data as we delve into supervised and unsupervised learning, reinforcement learning, and more. Discover practical applications in various domains like healthcare, finance, and autonomous vehicles. From introductory guides to advanced techniques, we’re here to help you demystify machine learning and unlock its potential. Join us on this journey as we unravel the secrets of machine learning and empower you to build intelligent systems that can analyze data, make predictions, and drive innovation.
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? Let me provide a real, personal example. We fine-tuned a 7B parameter model which completely blows foundation models out of the water, but just for this very narrow subtask: Filling out synoptic reporting templates for breast cancer. This is a hellishly difficult task with complex input formats, branching logic, and fields that must appear in …
Building an agent that works in a notebook takes an afternoon. Getting that same agent to survive real traffic, recover from a crash at 3 am, and not leak someone else’s data while it runs large language model (LLM)-generated code is a different job entirely, and it’s the job most teams underestimate. Only a …
5 Tools for Building and Deploying AI Agents in Production Read More »
TL;DR a full working implementation in pure Python, with real benchmark numbers. What I did: built a controlled experiment that isolates one variable, relationship density, from everything usually confounded with it, using a fully deterministic agent policy instead of live model calls. What I found: more communication pathways between agents did not automatically mean better …
Graph Engineering Isn’t About More Connections — It’s About Which Ones Get Used Read More »
# Introduction Data cleaning is rarely interesting, but it does consume the majority of a data professional’s time. Before any model trains or dashboard renders, someone has to wrestle mismatched column names, nulls scattered across a billion rows, type inconsistencies, duplicate records, and strings that almost match but don’t. Standard pandas handles a lot of this, …
5 Python Libraries That Make Data Cleaning More Enjoyable Read More »
, the good folks at DuckDB released a database communication protocol called Quack. Its main aim was to allow DuckDB databases held on different servers to communicate with each other over HTTP in a client/server arrangement and allow them to read and write each others data. In other words, using the Quack protocol, DuckDB sitting …
Running SQL Concurrently Across Three Remote DuckDB Servers with Quack Read More »
Web scraping is the process of collecting information from websites automatically. A normal scraper usually extracts raw text, HTML elements, or the full page content. But when you are building AI agents or large language model (LLM) applications, sending the entire webpage to the model is not always the best approach. A better way …
How to Build a Simple AI Web Scraper with Python Read More »
3.7 Flash shows strong gains over 3.6 Flash in coding tasks like debugging and issue resolution. It also achieves higher first-pass code accuracy and has improved performance in generating production-ready code as seen in FrontierCode 1.1 Main (43.6% vs 34.4%) and DeepSWE v1.1 (65.3% vs 49.0%). In web development, 3.7 Flash generates more functional layouts …
Code every day to get tasks done, mostly related to programming. Claude Code is great when you need to perform specific tasks. For example, if you’re assigned a specific task to do or if you’re working on a project. However, Claude Code and other similar coding agents don’t work as well in proactive work. So …
Installing Python used to mean visiting a website, downloading the correct installer, checking the right boxes, and making sure Python was added to PATH. Today, it is much easier. In many cases, you can simply open your terminal, type a single command, and Python is installed. That is now true across Windows, Linux, and …
handed the entire £20,000 budget to a single channel. Add one rule that forced a little onto a second channel and it complied, but it also returned a quiet negative number beside that rule. The number meant the floor you set is working against you, and it said exactly what that costs. Many optimisation workflows …
