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#General #Development #Mobile Development #Cloud & DevOps #Cybersecurity & Privacy #AI & Data Science #Hardware & Gadgets #Design & UX“My biggest lesson was realizing that domain expertise matters more than algorithmic complexity.“
Claudia Ng reflects on real-world ML lessons, mentoring newcomers, and her journey from corporate ML to freelance AI. The post “My biggest lesson was realizing that domain expertise matters more than algorithmic complexity.“ appeared first on Towards Data Science.
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The Future of LLM Development is Open Source
We’re entering a phase where openness equals power. The walls are coming down.
All You Need is Ollama’s New App
Effectively increase your productivity with local LLMs using Ollama's new app.
How to Use LLMs for Powerful Automatic Evaluations
A beginner-friendly introduction to LLM-as-a-Judge The post How to Use LLMs for Powerful Automatic Evaluations appeared first on Towards Data Science.
Data Mesh Diaries: Realities from Early Adopters
Early-adopter realities gathered from real data mesh implementations The post Data Mesh Diaries: Realities from EarlyAdopters appeared first on Towards Data Science.
Tips for Setting Expectations in AI Projects
If you want your AI project to succeed, mastering expectation management comes first. When working with AI projets, uncertainty isn’t just a side effect, it can make or break the entire initiative. Most people impacted by AI projects don’t fully understand how AI works, or that errors are not only inevitable but actually a natural […] The post Tips for Setting Expectations in AI Projects appeared first on Towards Data...
A Bird’s-Eye View of Linear Algebra: Why Is Matrix Multiplication Like That?
Since the way we manipulate high-dimensional vectors is primarily matrix multiplication, it isn’t a stretch to say it is the bedrock of the modern AI revolution. The post A Bird’s-Eye View of Linear Algebra: Why Is Matrix Multiplication Like That? appeared first on Towards Data Science.
Diffusion Models Demystified: Understanding the Tech Behind DALL-E and Midjourney
Understand the technical aspects of one of the most popular image generation model architectures.
10 GitHub Repositories to Master Frontend Development
Mastering frontend development essential, and these 10 GitHub repositories offer the best resources, tools, and project ideas to help you in this pursuit.
Reducing Time to Value for Data Science Projects: Part 4
Embrace your inner software developer The post Reducing Time to Value for Data Science Projects: Part 4 appeared first on Towards Data Science.
Model Predictive Control Basics
A hands-on tutorial with Python and CasADi The post Model Predictive Control Basics appeared first on Towards Data Science.
Coconut: A Framework for Latent Reasoning in LLMs
Explaining Coconut (Training Large Language Models to Reason in a Continuous Latent Space) in simple terms The post Coconut: A Framework for Latent Reasoning inLLMs appeared first on Towards Data Science.
A Refined Training Recipe for Fine-Grained Visual Classification
How FGVC aims to recognize images belonging to multiple subordinate categories of a super-category The post A Refined Training Recipe for Fine-Grained Visual Classification appeared first on Towards Data Science.
Fine-Tune Your Topic Modeling Workflow with BERTopic
Learn how to fine-tune BERTopic settings for more focused, reproducible, and interpretable results The post Fine-Tune Your Topic Modeling Workflow with BERTopic appeared first on Towards Data Science.
Getting Started with Neo4j: Installation and Setup Guide
Learn how to install and set up Neo4j. This article will help you start using Neo4j to explore connected data.
How to Go From Text to SQL with LLMs
This is a step-by-step guide to prompting LLMs in natural language and getting SQL code.
Making Sense of Text with Decision Trees
In this article, you will learn: • Build a decision tree classifier for spam email detection that analyzes text data.
Estimating from No Data: Deriving a Continuous Score from Categories
A walk-through of and the maths behind using low-capacity networks to acquire fine-grained scoring when only categorical labelling is available for training. We use it to predict the severity of an infection on a scale based on information on just rough outcomes in previous cases. The post Estimating from No Data: Deriving a Continuous Score from Categories appeared first on Towards Data Science.
Introducing Google’s LangExtract tool
Do RAG without doing RAG with this powerful new NLP and data extraction library The post Introducing Google’s LangExtract tool appeared first on Towards Data Science.
From Genes to Neural Networks: Understanding and Building NEAT (Neuro-Evolution of Augmenting Topologies) from Scratch
Practical Neuroevolution: Reproducing NEAT’s Innovations and Code Walkthrough The post From Genes to Neural Networks: Understanding and Building NEAT (Neuro-Evolution of Augmenting Topologies) fromScratch appeared first on Towards Data Science.
AI-Driven Data Governance and Compliance Best Practices
AI is steadily changing data governance by empowering businesses to stay compliant and agile without getting bogged down by manual tasks.
5 Useful Python Scripts for Busy Data Scientists
Tired of spending hours on repetitive data tasks? These Python scripts can come in handy for the overworked data scientist looking to simplify daily workflows.
10 Agentic AI Key Concepts Explained
Explore 10 agentic AI terms and concepts that are key to understanding the latest AI paradigm everyone wants to talk about — but not everyone clearly understands.
How to Interpret Your XGBoost Model: A Practical Guide to Feature Importance
One of the most widespread machine learning techniques is XGBoost (Extreme Gradient Boosting).
Agentic AI Hands-On in Python: A Video Tutorial
Introducing a four-hour video workshop on agentic AI engineering from Jon Krohn and Edward Donner.
How to Design Machine Learning Experiments — the Right Way
The key to successful ML projects isn't always more resources The post How to Design Machine Learning Experiments — the Right Way appeared first on Towards Data Science.
How to Write Insightful Technical Articles
Learn how to write informative technical articles The post How to Write Insightful Technical Articles appeared first on Towards Data Science.
Generating Structured Outputs from LLMs
An overview of popular techniques to confine LLMs' output to a predefined schema The post Generating Structured Outputs from LLMs appeared first on Towards Data Science.
Demystifying Cosine Similarity
Mathematical intuition and practical considerations for NLP scenarios The post Demystifying Cosine Similarity appeared first on Towards Data Science.
Grok’s Share and Claude’s Leak: 5 Things We Can Learn From System Prompts
The foundational instructions that govern the operation and user/model interaction of language models (also known as system prompts) are able to offer insights into how we — as users, AI practitioners, and developers — can optimize our interactions, approach future model advancements, and develop useful language model-driven applications.
AI-Powered Feature Engineering with n8n: Scaling Data Science Intelligence
Generate strategic feature engineering recommendations using AI-powered workflows in n8n.
Time Series Forecasting Made Simple (Part 3.2): A Deep Dive into LOESS-Based Smoothing
Explore how STL uses LOESS smoothing to extract trend and seasonal components. The post Time Series Forecasting Made Simple (Part 3.2): A Deep Dive into LOESS-Based Smoothing appeared first on Towards Data Science.
7 Pandas Tricks for Time-Series Feature Engineering
Feature engineering is one of the most important steps when it comes to building effective machine learning models, and this is no less important when dealing with time-series data.
Agentic AI: On Evaluations
Metrics to track for RAG and agents, plus the frameworks that help The post Agentic AI: On Evaluations appeared first on Towards Data Science.
Finding Golden Examples: A Smarter Approach to In-Context Learning
From random example selection to systematic AuPair generation— how to make your LLM prompts actually work The post Finding Golden Examples: A Smarter Approach to In-Context Learning appeared first on Towards Data Science.