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Understanding the Tech Stack Behind Generative AI
From foundation models to vector databases and AI agents β what makes modern AI work The post Understanding the Tech Stack Behind Generative AI appeared first on Towards Data Science.
Published on: April 01, 2025 | Source:
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My Learning to Be Hired Again After a Year⦠Part 2
One year later: what I learned still matters The post My Learning to Be Hired Again After a Year⦠Part 2 appeared first on Towards Data Science.
Published on: March 31, 2025 | Source:VIP Cheatsheet: Transformers & Large Language Models
Learn more about this handy resource created by Afshine and Shervine Amidi for Stanford's CME 295 course.
Published on: March 31, 2025 | Source:3 Ways Vibe Coding and AI-Assisted Development Are 2 Different Things
Vibe coding and AI-assisted development are two trendy terms in today's tech jargon.
Published on: March 31, 2025 | Source:Advanced Q&A Features with DistilBERT
This post is divided into three parts; they are: β’ Using DistilBERT Model for Question Answering β’ Evaluating the Answer β’ Other Techniques for Improving the Q&A Capability BERT (Bidirectional Encoder Representations from Transformers) was trained to be a general-purpose language model that can understand text.
Published on: March 29, 2025 | Source:The Art of Hybrid Architectures
Combining CNNs and Transformers to Elevate Fine-Grained Visual Classification The post The Art of Hybrid Architectures appeared first on Towards Data Science.
Published on: March 29, 2025 | Source:A Little More Conversation, A Little Less Action β A Case Against Premature Data Integration
Running a large data integration project before embarking on the ML part is easily a bad idea, because you integrate data without knowing its use. The chances that the data is going to be fit for purpose in some future ML use case is slim, at best This article shows how having people talking together helps avoid the trap of premature data integration in ML projects, optimising value for money. The post A Little More...
Published on: March 29, 2025 | Source:Master the 3D Reconstruction Process: A Step-by-Step Guide
Learn the complete 3D reconstruction pipeline from feature extraction to dense matching. Master photogrammetry with Python code examples and open-source tools. The post Master the 3D Reconstruction Process: A Step-by-Step Guide appeared first on Towards Data Science.
Published on: March 28, 2025 | Source:AI Agents from Zero to Hero β Part 3
Build from scratch using only Ollama (no GPU, no APIKEY) The post AI Agents from Zero to Hero β Part 3 appeared first on Towards Data Science.
Published on: March 28, 2025 | Source:From Physics to Probability: Hamiltonian Mechanics for Generative Modeling and MCMC
Hamiltonian mechanics is a way to describe how physical systems, like planets or pendulums, move over time, focusing on energy rather than just forces. By reframing complex dynamics through energy lenses, this 19th-century physics framework now powers cutting-edge generative AI. It uses generalized coordinates ( q ) (like position) and their conjugate momenta ( p ) (related to momentum), forming a phase space that...
Published on: March 28, 2025 | Source:How to Format Your TDS Draft: A Quick(ish) Guide
Everything you need to know about creating a draft on our Contributor Portal The post How to Format Your TDS Draft: A Quick(ish) Guide appeared first on Towards Data Science.
Published on: March 28, 2025 | Source:A Gentle Introduction to Attention and Transformer Models
This post is divided into three parts; they are: β’ Origination of the Transformer Model β’ The Transformer Architecture β’ Variations of the Transformer Architecture Transformer architecture originated from the 2017 paper "Attention is All You Need" by Vaswani et al.
Published on: March 28, 2025 | Source:Building a Recommender System From Scratch with Matrix Factorization in Python
In this article, we will build step by step a movie recommender system in Python, based on matrix factorization.
Published on: March 28, 2025 | Source:7 GitHub Projects to Master Machine Learning
Learn model serving, CI/CD, ML orchestration, model deployment, local AI, and Docker to streamline ML workflows, automate pipelines, and deploy scalable, portable AI solutions effectively.
Published on: March 28, 2025 | Source:7 GitHub Projects to Master Machine Learning Operations
Learn model serving, CI/CD, ML orchestration, model deployment, local AI, and Docker to streamline ML workflows, automate pipelines, and deploy scalable, portable AI solutions effectively.
Published on: March 28, 2025 | Source:Data Science: From School to Work, Part III
Good practices for Python error handling and logging The post Data Science: From School to Work, Part III appeared first on Towards Data Science.
Published on: March 28, 2025 | Source:Japanese-Chinese Translation with GenAI: What Works and What Doesnβt
Evaluating GenAI in Japanese-Chinese translation: current limits and opportunities The post Japanese-Chinese Translation with GenAI: What Works and What Doesnβt appeared first on Towards Data Science.
Published on: March 27, 2025 | Source:Talk to Videos
Developing an interactive AI application for video-based learning in education and business The post Talk to Videos appeared first on Towards Data Science.
Published on: March 27, 2025 | Source:Why You Arenβt Getting Hired as a Data Science in 2025
Some say data science is dying, while others are more concerned with the imminent death of their own career.
Published on: March 27, 2025 | Source:A Guide to Integrating ChatGPT with Google Sheets
This guide provides a detailed, step-by-step explanation of how to connect ChatGPT with Google Sheets, along with practical examples and advanced features to make the most of this integration.
Published on: March 27, 2025 | Source:Automate Supply Chain Analytics Workflows with AI Agents usingΒ n8n
What if you could automate complete supply chain analytics workflows with low-code solutions? The post Automate Supply Chain Analytics Workflows with AI Agents usingn8n appeared first on Towards Data Science.
Published on: March 26, 2025 | Source:AI Agents from Zero to Hero β Part 2
Build from scratch using only Ollama (no GPU, no APIKEY) The post AI Agents from Zero to Hero β Part 2 appeared first on Towards Data Science.
Published on: March 26, 2025 | Source:Uncertainty Quantification in Machine Learning with an Easy Python Interface
The ML Uncertainty Package The post Uncertainty Quantification in Machine Learning with an Easy Python Interface appeared first on Towards Data Science.
Published on: March 26, 2025 | Source:The Beginnerβs Guide to Machine Learning with Rust
Machine learning has become an essential tool for solving complex problems across various domains, from finance to healthcare.
Published on: March 26, 2025 | Source:Building an Automatic Speech Recognition System with PyTorch & Hugging Face
Check out this step-by-step guide to building a speech-to-text system with PyTorch & Hugging Face.
Published on: March 26, 2025 | Source:Trae: Adaptive AI Code Editor
In this article, we will explore Trae, a powerful adaptive AI code editor, its key features, setup process, and tips for maximizing productivity.
Published on: March 26, 2025 | Source:The Ultimate AI/ML Roadmap For Beginners
How to learn AI/ML from scratch The post The Ultimate AI/ML Roadmap For Beginners appeared first on Towards Data Science.
Published on: March 26, 2025 | Source:Attractors in Neural Network Circuits:Β Beauty and Chaos
Neural networks under a different lens: generating basins of attraction in a shift register NN The post Attractors in Neural Network Circuits:Beauty and Chaos appeared first on Towards Data Science.
Published on: March 25, 2025 | Source:Data-Driven March Madness Predictions
How to optimize your bracket systematically, no college basketball knowledge required The post Data-Driven March Madness Predictions appeared first on Towards Data Science.
Published on: March 25, 2025 | Source:Testing the Power of Multimodal AI Systems in Reading and Interpreting Photographs, Maps, Charts andΒ More
Can multimodal AI systems consisting in LLMs with vision capabilities understand figures and extract information from them? The post Testing the Power of Multimodal AI Systems in Reading and Interpreting Photographs, Maps, Charts andMore appeared first on Towards Data Science.
Published on: March 25, 2025 | Source:A Clear Intro to MCP (Model Context Protocol) with Code Examples
MCP is a way to democratize access to tools for AI Agents. In this article we cover the fundamental components of MCP, how they work together, and a code example of how MCP works in practice. The post A Clear Intro to MCP (Model Context Protocol) with Code Examples appeared first on Towards Data Science.
Published on: March 25, 2025 | Source:Gemini 2.5: Our most intelligent AI model
Gemini 2.5 is our most intelligent AI model, now with thinking built in.
Published on: March 25, 2025 | Source:Processing a Directory of CSVs Too Big for Memory with Dask
Learn how to process the big data in the CSV format.
Published on: March 25, 2025 | Source:A Gentle Introduction to Graph Neural Networks in Python
Graph neural networks (GNNs) can be pictured as a special class of neural network models where data are structured as graphs β both training data used to train the model and real-world data used for inference β rather than fixed-size vectors or grids like image, sequences, or instances of tabular data.
Published on: March 25, 2025 | Source:Land Your Dream Machine Learning Job in 2025
In this article, I will go through 5 pointers on how to help you secure your dream job.
Published on: March 25, 2025 | Source: