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Dimensionality reduction in linear regression: classical stepwise methods and a Python application on real-world data
The post Stepwise Selection Made Simple: Improve Your Regression Models in Python appeared first on Towards Data Science.
From theoretical puzzles to practical applications
The post Graph Coloring for Data Science: A Comprehensive Guide appeared first on Towards Data Science.
Docker makes data science workflows more consistent and portable. This guide breaks it down into five simple, practical steps.
How hyperparameter tuning visually changes decision trees
The post A Visual Guide to Tuning Decision-Tree Hyperparameters appeared first on Towards Data Science.
In this article, we will explore seven simple machine learning projects that will help you learn important skills and improve your career.
VaxSeer uses machine learning to predict virus evolution and antigenicity, aiming to make vaccine selection more accurate and less reliant on guesswork.
The following article comes from two blog posts by Drew Breunig: “How Long Contexts Fail” and “How to Fix Your Contexts.” Managing Your Context Is the Key to Successful Agents As frontier model context windows continue to grow,1 with many supporting up to 1 million tokens, I see many excited discussions about how long-context windows […]
Understand how open source can help you unravel air quality
The post Air for Tomorrow: Why Openness in Air Quality Research and Implementation Matters for Global Equity appeared first on Towards Data Science.
When working with machine learning on structured data, two algorithms often rise to the top of the shortlist: random forests and gradient boosting .
While superconducting qubits are great at fast calculations, they struggle to store information for long periods. A team at Caltech has now developed a clever solution: converting quantum information into sound waves. By using a tiny device that acts like a miniature tuning fork, the researchers were able to extend quantum memory lifetimes up to 30 times longer than before. This breakthrough could pave the way toward practical, scalable quantum computers that can both compute and remember.
Explore how Agentic AI is reshaping the tech careers, from data to decision-making, and how professionals can prepare for the future of work
The post Get AI-Ready: How to Prepare for a World of Agentic AI as Tech Professionals appeared first on Towards Data Science.
The books, courses, and resources I used in my journey.
The post Everything I Studied to Become a Machine Learning Engineer (No CS Background) appeared first on Towards Data Science.
Google is investing an additional $9 billion in Virginia through 2026 in cloud and AI infrastructure. As we expand our local presence, including a new data center in Che…
An intuitive guide to stationarity in a time series
The post Time Series Forecasting Made Simple (Part 4.1): Understanding Stationarity in a Time Series appeared first on Towards Data Science.
In this post, we announce that Mercury and Mercury Coder foundation models from Inception Labs are now available through Amazon Bedrock Marketplace and Amazon SageMaker JumpStart. We demonstrate how to deploy these ultra-fast diffusion-based language models that can generate up to 1,100 tokens per second on NVIDIA H100 GPUs, and showcase their capabilities in code generation and tool use scenarios.
Language models are becoming really good. But where did they come from?
The post A Brief History of GPT Through Papers appeared first on Towards Data Science.
Separating AI reality from hyped-up fiction isn’t always easy. That’s why we’ve created the AI Hype Index—a simple, at-a-glance summary of everything you need to know about the state of the industry. Using AI to improve our health and well-being is one of the areas scientists and researchers are most excited about. The last month…
Rust lets developers build fast and reliable data tools. This article shows how to use Rust’s features for high-performance data processing.
Nano-Banana revealed, Claude in Chrome, AI deadbots, deepfake con, and more...
Salesforce launches CRMArena-Pro, a simulated enterprise AI testing platform, to address the 95% failure rate of AI pilots and improve agent reliability, performance, and security in real-world business deployments.
Panning a spherical image is just a horizontal roll, but tilting it vertically is much trickier. Let's see the math!
The post The Math You Need to Pan and Tilt 360° Images appeared first on Towards Data Science.
Cybercriminals are increasingly using generative AI tools to fuel their attacks, with new research finding instances of AI being used to develop ransomware.
Tired of starting/stopping different models every time you want to test something? Let Llama-Swap handle that for you.
In this article, you will learn: • The fundamental difference between traditional regression, which uses single fixed values for its parameters, and Bayesian regression, which models them as probability distributions.
When I picked up my daughter from summer camp, we settled in for an eight-hour drive through the Appalachian mountains, heading from North Carolina to her grandparents’ home in Kentucky. With little to no cell service for much of the drive, we enjoyed the rare opportunity to have a long, thoughtful conversation, uninterrupted by devices.…
MCP—the Model Context Protocol introduced by Anthropic in November 2024—is an open standard for connecting AI assistants to data sources and development environments. It’s built for a future where every AI assistant is wired directly into your environment, where the model knows what files you have open, what text is selected, what you just typed, […]
Memp takes inspiration from human cognition to give LLM agents "procedural memory" that can adapt to new tasks and environments.
Anthropic launches a limited pilot of Claude for Chrome, allowing its AI to control web browsers while raising critical concerns about security and prompt injection attacks.
Global enterprises Block and GlaxoSmithKline (GSK) are exploring AI agent proof of concepts in financial services and drug discovery.
Anthropic faced the prospect of more than $1 trillion in damages, a sum that could have threatened the company’s survival if the case went to trial.