Category: data-science
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Federated Learning and Custom Aggregation Schemes
Federated Learning and Custom Aggregation Schemes A practical guide to designing and analyzing robust aggregation strategies The post Federated Learning and Custom Aggregation Schemes appeared first on Towards Data Science. Salman Toor Go to original source
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Hidden Gems in NumPy: 7 Functions Every Data Scientist Should Know
Hidden Gems in NumPy: 7 Functions Every Data Scientist Should Know I’ve been learning data analytics for a year now. So far, I can consider myself confident in SQL and Power BI. The transition to Python has been quite exciting. I’ve been exposed to some neat and smarter approaches to data analysis. After brushing up…
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How I Tailored the Resume That Landed Me $100K+ Data Science and ML Offers
How I Tailored the Resume That Landed Me $100K+ Data Science and ML Offers How to write a data science and machine learning resume that actually lands jobs. The post How I Tailored the Resume That Landed Me $100K+ Data Science and ML Offers appeared first on Towards Data Science. Egor Howell Go to original…
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Conceptual Frameworks for Data Science Projects
Conceptual Frameworks for Data Science Projects An overview of common framework types and a simple process for building custom frameworks The post Conceptual Frameworks for Data Science Projects appeared first on Towards Data Science. Chinmay Kakatkar Go to original source
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Python 3.14 and the End of the GIL
Python 3.14 and the End of the GIL Exploring the opportunities and challenges of a GIL-free Python The post Python 3.14 and the End of the GIL appeared first on Towards Data Science. Thomas Reid Go to original source
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How to Classify Lung Cancer Subtype from DNA Copy Numbers Using PyTorch
How to Classify Lung Cancer Subtype from DNA Copy Numbers Using PyTorch A step-by-step introduction to understanding cancer from the perspective of a data scientist. The post How to Classify Lung Cancer Subtype from DNA Copy Numbers Using PyTorch appeared first on Towards Data Science. Adam Streck Go to original source
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How I Used Machine Learning to Predict 41% of Project Delays Before They Happened
How I Used Machine Learning to Predict 41% of Project Delays Before They Happened How data science can help project managers anticipate risks and save time The post How I Used Machine Learning to Predict 41% of Project Delays Before They Happened appeared first on Towards Data Science. Yassin Zehar Go to original source
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First Principles Thinking for Data Scientists
First Principles Thinking for Data Scientists The mindset that turns good data scientists into great ones The post First Principles Thinking for Data Scientists appeared first on Towards Data Science. Greg Rafferty Go to original source
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Building A Successful Relationship With Stakeholders
Building A Successful Relationship With Stakeholders Show your value by moving beyond the technical The post Building A Successful Relationship With Stakeholders appeared first on Towards Data Science. Kristopher McGlinchey Go to original source
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Why AI Still Can’t Replace Analysts: A Predictive Maintenance Example
Why AI Still Can’t Replace Analysts: A Predictive Maintenance Example Learn about the limitations of AI in analytics through the example of bearing vibration data analysis The post Why AI Still Can’t Replace Analysts: A Predictive Maintenance Example appeared first on Towards Data Science. Illia Smoliienko Go to original source
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How to Spin Up a Project Structure with Cookiecutter
How to Spin Up a Project Structure with Cookiecutter If you’re anything like me, “procrastination” might as well be your middle name. There’s always that nagging hesitation before starting a new project. Just thinking about setting up the project structure, creating documentation, or writing a decent README is enough to trigger yawns. It feels like…
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10 Data + AI Observations for Fall 2025
10 Data + AI Observations for Fall 2025 What’s happening—and what’s next— for data and AI at the close of 2025. The post 10 Data + AI Observations for Fall 2025 appeared first on Towards Data Science. Barr Moses Go to original source
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Past is Prologue: How Conversational Analytics Is Changing Data Work
Past is Prologue: How Conversational Analytics Is Changing Data Work The future of reporting will be about encoding the value proposition of a product into prompt design. The post Past is Prologue: How Conversational Analytics Is Changing Data Work appeared first on Towards Data Science. Whitney Marks Go to original source
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How the Rise of Tabular Foundation Models Is Reshaping Data Science
How the Rise of Tabular Foundation Models Is Reshaping Data Science A turning point for data analysis? The post How the Rise of Tabular Foundation Models Is Reshaping Data Science appeared first on Towards Data Science. Pirmin Lemberger Go to original source
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Know Your Real Birthday: Astronomical Computation and Geospatial-Temporal Analytics in Python
Know Your Real Birthday: Astronomical Computation and Geospatial-Temporal Analytics in Python A hands-on walkthrough using skyfield, timezonefinder, geopy, and pytz, and further practical applications The post Know Your Real Birthday: Astronomical Computation and Geospatial-Temporal Analytics in Python appeared first on Towards Data Science. Chinmay Kakatkar Go to original source
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Data Visualization Explained (Part 3): The Role of Color
Data Visualization Explained (Part 3): The Role of Color A simple and powerful guide to using color for more impactful data stories. The post Data Visualization Explained (Part 3): The Role of Color appeared first on Towards Data Science. Murtaza Ali Go to original source
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This Puzzle Shows Just How Far LLMs Have Progressed in a Little Over a Year
This Puzzle Shows Just How Far LLMs Have Progressed in a Little Over a Year What took GPT-4o 2 hours to solve, Sonnet 4.5 does in 5 seconds The post This Puzzle Shows Just How Far LLMs Have Progressed in a Little Over a Year appeared first on Towards Data Science. Thomas Reid Go to original source
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How I Used ChatGPT to Land My Next Data Science Role
How I Used ChatGPT to Land My Next Data Science Role Practical AI hacks for every stage of the job search — with real prompts and examples The post How I Used ChatGPT to Land My Next Data Science Role appeared first on Towards Data Science. Yu Dong Go to original source
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Plotly Dash — A Structured Framework for a Multi-Page Dashboard
Plotly Dash — A Structured Framework for a Multi-Page Dashboard An easy starting point for larger and more complicated Dash dashboards The post Plotly Dash — A Structured Framework for a Multi-Page Dashboard appeared first on Towards Data Science. Michael Clayton Go to original source
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Classical Computer Vision and Perspective Transformation for Sudoku Extraction
Classical Computer Vision and Perspective Transformation for Sudoku Extraction Why you shouldn’t overcomplicate solutions to simple problems The post Classical Computer Vision and Perspective Transformation for Sudoku Extraction appeared first on Towards Data Science. Florian Trautweiler Go to original source
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Building a Command-Line Quiz Application in R
Building a Command-Line Quiz Application in R Practice control flow, input handling, and functions in R by creating an interactive quiz game. The post Building a Command-Line Quiz Application in R appeared first on Towards Data Science. Benjamin Nweke Go to original source
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Real-Time Intelligence in Microsoft Fabric: The Ultimate Guide
Real-Time Intelligence in Microsoft Fabric: The Ultimate Guide Once upon a time, handling streaming data was considered an avant-garde approach. Since the introduction of relational database management systems in the 1970s and traditional data warehousing systems in the late 1980s, all data workloads began and ended with the so-called batch processing. Batch processing relies on the concept of…
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Prediction vs. Search Models: What Data Scientists Are Missing
Prediction vs. Search Models: What Data Scientists Are Missing How do platform firms set prices and make money? The post Prediction vs. Search Models: What Data Scientists Are Missing appeared first on Towards Data Science. Derek Tran Go to original source
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What Makes a Language Look Like Itself?
What Makes a Language Look Like Itself? How simple statistics reveal the visual fingerprints of 20 languages The post What Makes a Language Look Like Itself? appeared first on Towards Data Science. Kenneth McCarthy Go to original source
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Temporal-Difference Learning and the Importance of Exploration: An Illustrated Guide
Temporal-Difference Learning and the Importance of Exploration: An Illustrated Guide Comparing model-free and model-based RL methods on a dynamic grid world The post Temporal-Difference Learning and the Importance of Exploration: An Illustrated Guide appeared first on Towards Data Science. Ryan Pégoud Go to original source
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Are Foundation Models Ready for Your Production Tabular Data?
Are Foundation Models Ready for Your Production Tabular Data? A complete review of architectures to make zero-shot predictions in the most common types of datasets. The post Are Foundation Models Ready for Your Production Tabular Data? appeared first on Towards Data Science. Carmen Adriana Martínez Barbosa Go to original source
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Data Visualization Explained (Part 2): An Introduction to Visual Variables
Data Visualization Explained (Part 2): An Introduction to Visual Variables A non-technical and accessible guide to the underlying concept behind visual design: visual encoding channels The post Data Visualization Explained (Part 2): An Introduction to Visual Variables appeared first on Towards Data Science. Murtaza Ali Go to original source
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Beyond ROC-AUC and KS: The Gini Coefficient, Explained Simply
Beyond ROC-AUC and KS: The Gini Coefficient, Explained Simply Understanding Gini and Lorenz curves for smarter model evaluation The post Beyond ROC-AUC and KS: The Gini Coefficient, Explained Simply appeared first on Towards Data Science. Nikhil Dasari Go to original source
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The Machine Learning Lessons I’ve Learned This Month
The Machine Learning Lessons I’ve Learned This Month September 2025: library or self-made, Ditto and Launchbar, reading widely and deeply The post The Machine Learning Lessons I’ve Learned This Month appeared first on Towards Data Science. Pascal Janetzky Go to original source
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Eulerian Melodies: Graph Algorithms for Music Composition
Eulerian Melodies: Graph Algorithms for Music Composition Conceptual overview and an end-to-end Python implementation The post Eulerian Melodies: Graph Algorithms for Music Composition appeared first on Towards Data Science. Chinmay Kakatkar Go to original source
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Why MissForest Fails in Prediction Tasks: A Key Limitation You Need to Keep in Mind
Why MissForest Fails in Prediction Tasks: A Key Limitation You Need to Keep in Mind Why the original MissForest algorithm cannot be directly applied for predictive modeling, and how MissForestPredict solves this problem The post Why MissForest Fails in Prediction Tasks: A Key Limitation You Need to Keep in Mind appeared first on Towards Data…
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Building a Video Game Recommender System with FastAPI, PostgreSQL, and Render: Part 2
Building a Video Game Recommender System with FastAPI, PostgreSQL, and Render: Part 2 Deploying a FastAPI + PostgreSQL recommender system as a web application on Render The post Building a Video Game Recommender System with FastAPI, PostgreSQL, and Render: Part 2 appeared first on Towards Data Science. Lucas See Go to original source
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Building Video Game Recommender Systems with FastAPI, PostgreSQL, and Render: Part 1
Building Video Game Recommender Systems with FastAPI, PostgreSQL, and Render: Part 1 Designing a video game recommendations service with Steams API The post Building Video Game Recommender Systems with FastAPI, PostgreSQL, and Render: Part 1 appeared first on Towards Data Science. Lucas See Go to original source
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Decoding Nonlinear Signals In Large Observational Datasets
Decoding Nonlinear Signals In Large Observational Datasets Rain, snow, or something In between? The post Decoding Nonlinear Signals In Large Observational Datasets appeared first on Towards Data Science. Fraser King Go to original source
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The Art of Asking Good Questions
The Art of Asking Good Questions As a data scientist, are you driving product decisions? Or just supporting them? The right questions can turn AI from a threat into your career’s best ally. Here’s how to start asking them. The post The Art of Asking Good Questions appeared first on Towards Data Science. Greg Rafferty…
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Why Are Marketers Turning To Quasi Geo-Lift Experiments? (And How to Plan Them)
Why Are Marketers Turning To Quasi Geo-Lift Experiments? (And How to Plan Them) Are “quasi” geo-lift experiments the missing piece for your marketing science function? The post Why Are Marketers Turning To Quasi Geo-Lift Experiments? (And How to Plan Them) appeared first on Towards Data Science. Tomas Jancovic Go to original source
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How to Connect an MCP Server for an AI-Powered, Supply-Chain Network Optimization Agent
How to Connect an MCP Server for an AI-Powered, Supply-Chain Network Optimization Agent From prompt to strategic decision-making: MCP-powered agents for cost-efficient, reliable and sustainable supply chain network design. The post How to Connect an MCP Server for an AI-Powered, Supply-Chain Network Optimization Agent appeared first on Towards Data Science. Samir Saci Go to original…
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The Kolmogorov–Smirnov Statistic, Explained: Measuring Model Power in Credit Risk Modeling
The Kolmogorov–Smirnov Statistic, Explained: Measuring Model Power in Credit Risk Modeling Understanding how banks use the KS statistic in loan approvals. The post The Kolmogorov–Smirnov Statistic, Explained: Measuring Model Power in Credit Risk Modeling appeared first on Towards Data Science. Nikhil Dasari Go to original source
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Integrating DataHub into Jira: A Practical Guide Using DataHub Actions
Integrating DataHub into Jira: A Practical Guide Using DataHub Actions A walkthrough of how to integrate metadata changes in DataHub into Jira workflows using the DataHub Actions Framework The post Integrating DataHub into Jira: A Practical Guide Using DataHub Actions appeared first on Towards Data Science. Jimin Kang Go to original source
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Data Visualization Explained: What It Is and Why It Matters
Data Visualization Explained: What It Is and Why It Matters A brief introduction to data visualization and its importance in today’s technological landscape. The post Data Visualization Explained: What It Is and Why It Matters appeared first on Towards Data Science. Murtaza Ali Go to original source
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The SyncNet Research Paper, Clearly Explained
The SyncNet Research Paper, Clearly Explained A Deep Dive into “Out of Time: Automated Lip Sync in the Wild” The post The SyncNet Research Paper, Clearly Explained appeared first on Towards Data Science. Aman Agrawal Go to original source
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From Python to JavaScript: A Playbook for Data Analytics in n8n with Code Node Examples
From Python to JavaScript: A Playbook for Data Analytics in n8n with Code Node Examples Learn the basics of JavaScript through tiny n8n Code node snippets for sales data analytics The post From Python to JavaScript: A Playbook for Data Analytics in n8n with Code Node Examples appeared first on Towards Data Science. Samir Saci…
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Analysis of Sales Shift in Retail with Causal Impact: A Case Study at Carrefour
Analysis of Sales Shift in Retail with Causal Impact: A Case Study at Carrefour Applying causal inference to measure the effect of product unavailability on retail sales at Carrefour The post Analysis of Sales Shift in Retail with Causal Impact: A Case Study at Carrefour appeared first on Towards Data Science. Thanh Liêm NGUYEN Go…
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ROC AUC Explained: A Beginner’s Guide to Evaluating Classification Models
ROC AUC Explained: A Beginner’s Guide to Evaluating Classification Models Understand how ROC curves and AUC help you go beyond accuracy with visuals and examples. The post ROC AUC Explained: A Beginner’s Guide to Evaluating Classification Models appeared first on Towards Data Science. Nikhil Dasari Go to original source
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Why Your A/B Test Winner Might Just Be Random Noise
Why Your A/B Test Winner Might Just Be Random Noise What a coach’s warm-up trial can teach us about running better experiments The post Why Your A/B Test Winner Might Just Be Random Noise appeared first on Towards Data Science. Pol Marin Go to original source
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A Visual Guide to Tuning Gradient Boosted Trees
A Visual Guide to Tuning Gradient Boosted Trees Introduction My previous posts looked at the bog-standard decision tree and the wonder of a random forest. Now, to complete the triplet, I’ll visually explore gradient boosted trees! There are a bunch of gradient boosted tree libraries, including XGBoost, CatBoost, and LightGBM. However, for this I’m going…
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The Rise of Semantic Entity Resolution
The Rise of Semantic Entity Resolution Semantic entity resolution uses language models to bring an increased level of automation to schema alignment, blocking (grouping records into smaller, efficient blocks for all-pairs comparison at quadratic, n² complexity), matching and even merging duplicate nodes and edges. In the past, entity resolution systems relied on statistical tricks such…
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No Peeking Ahead: Time-Aware Graph Fraud Detection
No Peeking Ahead: Time-Aware Graph Fraud Detection How to implement leak-free graph fraud detection The post No Peeking Ahead: Time-Aware Graph Fraud Detection appeared first on Towards Data Science. Erika G. Gonçalves Go to original source
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If we use AI to do our work – what is our job, then?
If we use AI to do our work – what is our job, then? Images. Text. Audio. There’s no modality that is not handled by AI. And AI systems reach even further, planning advertisement and marketing campaigns, automating social media postings, … Most of this was unthinkable a mere ten years ago. But then, the…
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A Focused Approach to Learning SQL
A Focused Approach to Learning SQL Data is everywhere, but how do you draw insights from it? Often, structured data is stored in relational databases, meaning collections of related tables of data. For instance, a company might store customer purchases in one table, customer demographics in another, and suppliers in a third table. These tables…
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The Crucial Role of Color Theory in Data Analysis and Visualization
The Crucial Role of Color Theory in Data Analysis and Visualization How research-backed color principles improved clarity and storytelling in my dashboards The post The Crucial Role of Color Theory in Data Analysis and Visualization appeared first on Towards Data Science. Benjamin Nweke Go to original source
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Is Your Training Data Representative? A Guide to Checking with PSI in Python
Is Your Training Data Representative? A Guide to Checking with PSI in Python Comparing Variable Distributions Between Two Datasets Using Population Stability Index (PSI) and Cramér’s V. The post Is Your Training Data Representative? A Guide to Checking with PSI in Python appeared first on Towards Data Science. JUNIOR JUMBONG Go to original source
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When A Difference Actually Makes A Difference
When A Difference Actually Makes A Difference Bite-Sized Analytics for Business Decision-Makers (1) The post When A Difference Actually Makes A Difference appeared first on Towards Data Science. Mena Wang Go to original source
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How to Build an AI Budget-Planning Optimizer for Your 2026 CAPEX Review: LangGraph, FastAPI, and n8n
How to Build an AI Budget-Planning Optimizer for Your 2026 CAPEX Review: LangGraph, FastAPI, and n8n Email → n8n → LangGraph → FastAPI: turning budget requests into optimised CAPEX portfolios that maximise ROI for decision-makers. The post How to Build an AI Budget-Planning Optimizer for Your 2026 CAPEX Review: LangGraph, FastAPI, and n8n appeared first…
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Exploring Merit Order and Marginal Abatement Cost Curve in Python
Exploring Merit Order and Marginal Abatement Cost Curve in Python To achieve the global temperature limit goals of 1.5°C by the end of the century set by the Paris Agreement, different institutions have come up with different scenarios. There is a consensus among the mitigation scenarios that the share of low-carbon technologies such as renewable energy needs…
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The End-to-End Data Scientist’s Prompt Playbook
The End-to-End Data Scientist’s Prompt Playbook Part 3: Prompts for docs, DevOps, and stakeholder communication The post The End-to-End Data Scientist’s Prompt Playbook appeared first on Towards Data Science. Sara Nobrega Go to original source
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Implementing the Coffee Machine in Python
Implementing the Coffee Machine in Python A beginner-friendly step-by-step guide to coding a Coffee Maker in Python The post Implementing the Coffee Machine in Python appeared first on Towards Data Science. Mahnoor Javed Go to original source
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The Beauty of Space-Filling Curves: Understanding the Hilbert Curve
The Beauty of Space-Filling Curves: Understanding the Hilbert Curve A quick journey from theory to implementation and application The post The Beauty of Space-Filling Curves: Understanding the Hilbert Curve appeared first on Towards Data Science. Paul Fröhling Go to original source
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AI Operations Under the Hood: Challenges and Best Practices
AI Operations Under the Hood: Challenges and Best Practices Building robust, reproducible, and reliable GenAI applications requires a framework of continuous improvement, rigorous evaluation, and systematic validation The post AI Operations Under the Hood: Challenges and Best Practices appeared first on Towards Data Science. Erika G. Gonçalves Go to original source
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Zero-Inflated Data: A Comparison of Regression Models
Zero-Inflated Data: A Comparison of Regression Models How to detect it and which model to choose. The post Zero-Inflated Data: A Comparison of Regression Models appeared first on Towards Data Science. Arnaud Capitaine Go to original source
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A Visual Guide to Tuning Random Forest Hyperparameters
A Visual Guide to Tuning Random Forest Hyperparameters How hyperparameter tuning visually changes random forests The post A Visual Guide to Tuning Random Forest Hyperparameters appeared first on Towards Data Science. James Gibbins Go to original source
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Hands On Time Series Modeling of Rare Events, with Python
Hands On Time Series Modeling of Rare Events, with Python This is how to model rare events occurrences in a time series in a few lines of code The post Hands On Time Series Modeling of Rare Events, with Python appeared first on Towards Data Science. Piero Paialunga Go to original source
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What Being a Data Scientist at a Startup Really Looks Like
What Being a Data Scientist at a Startup Really Looks Like What I learned about growth, visibility, and chaos over the past five years The post What Being a Data Scientist at a Startup Really Looks Like appeared first on Towards Data Science. Yu Dong Go to original source
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How to Scale Your AI Search to Handle 10M Queries with 5 Powerful Techniques
How to Scale Your AI Search to Handle 10M Queries with 5 Powerful Techniques Optimize your AI search with RAG, contextual retrieval and evaluations The post How to Scale Your AI Search to Handle 10M Queries with 5 Powerful Techniques appeared first on Towards Data Science. Eivind Kjosbakken Go to original source
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The Generalist: The New All-Around Type of Data Professional?
The Generalist: The New All-Around Type of Data Professional? Is over-specialization ending and are data generalists on the rise? The post The Generalist: The New All-Around Type of Data Professional? appeared first on Towards Data Science. Loizos Loizou Go to original source
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The Machine Learning Lessons I’ve Learned This Month
The Machine Learning Lessons I’ve Learned This Month August 2025: logging, lab notebooks, overnight runs The post The Machine Learning Lessons I’ve Learned This Month appeared first on Towards Data Science. Pascal Janetzky Go to original source
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How to Import Pre-Annotated Data into Label Studio and Run the Full Stack with Docker
How to Import Pre-Annotated Data into Label Studio and Run the Full Stack with Docker From VOC to JSON: Importing pre-annotations made simple The post How to Import Pre-Annotated Data into Label Studio and Run the Full Stack with Docker appeared first on Towards Data Science. Yagmur Gulec Go to original source
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Stepwise Selection Made Simple: Improve Your Regression Models in Python
Stepwise Selection Made Simple: Improve Your Regression Models in Python 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. JUNIOR JUMBONG Go to original source
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Graph Coloring for Data Science: A Comprehensive Guide
Graph Coloring for Data Science: A Comprehensive Guide From theoretical puzzles to practical applications The post Graph Coloring for Data Science: A Comprehensive Guide appeared first on Towards Data Science. Chinmay Kakatkar Go to original source
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A Visual Guide to Tuning Decision-Tree Hyperparameters
A Visual Guide to Tuning Decision-Tree Hyperparameters How hyperparameter tuning visually changes decision trees The post A Visual Guide to Tuning Decision-Tree Hyperparameters appeared first on Towards Data Science. James Gibbins Go to original source
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Air for Tomorrow: Why Openness in Air Quality Research and Implementation Matters for Global Equity
Air for Tomorrow: Why Openness in Air Quality Research and Implementation Matters for Global Equity 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. Prithviraj Pramanik Go to original source
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Get AI-Ready: How to Prepare for a World of Agentic AI as Tech Professionals
Get AI-Ready: How to Prepare for a World of Agentic AI as Tech Professionals 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…
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Everything I Studied to Become a Machine Learning Engineer (No CS Background)
Everything I Studied to Become a Machine Learning Engineer (No CS Background) 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. Egor Howell Go to original source
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Time Series Forecasting Made Simple (Part 4.1): Understanding Stationarity in a Time Series
Time Series Forecasting Made Simple (Part 4.1): Understanding Stationarity in a Time Series 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. Nikhil Dasari Go to original source
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Plato’s Cave and the Shadows of Data
Plato’s Cave and the Shadows of Data On truth, illusion, and the limits of what data can reveal The post Plato’s Cave and the Shadows of Data appeared first on Towards Data Science. Pol Marin Go to original source
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Using Google’s LangExtract and Gemma for Structured Data Extraction
Using Google’s LangExtract and Gemma for Structured Data Extraction Extracting structured information effectively and accurately from long unstructured text with LangExtract and LLMs The post Using Google’s LangExtract and Gemma for Structured Data Extraction appeared first on Towards Data Science. Kenneth Leung Go to original source
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Google’s URL Context Grounding: Another Nail in RAG’s Coffin?
Google’s URL Context Grounding: Another Nail in RAG’s Coffin? Google’s hot streak in AI-related releases continues unabated. Just a few days ago, it released a new tool for Gemini called URL context grounding. URL context grounding can be used stand-alone or combined with Google search grounding to conduct deep dives into internet content. What is…
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Three Essential Hyperparameter Tuning Techniques for Better Machine Learning Models
Three Essential Hyperparameter Tuning Techniques for Better Machine Learning Models Learn how to optimize your ML models for better results The post Three Essential Hyperparameter Tuning Techniques for Better Machine Learning Models appeared first on Towards Data Science. Rukshan Pramoditha Go to original source
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Cracking the Density Code: Why MAF Flows Where KDE Stalls
Cracking the Density Code: Why MAF Flows Where KDE Stalls Learn why autoregressive flows are the superior density estimation tool for high-dimensional data The post Cracking the Density Code: Why MAF Flows Where KDE Stalls appeared first on Towards Data Science. Zackary Nay Go to original source
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What If I Had AI in 2020: Rent The Runway Dynamic Pricing Model
What If I Had AI in 2020: Rent The Runway Dynamic Pricing Model Ever wondered how different things might have been if ChatGPT had existed at the start of Covid? Especially for data scientists who had to update their forecast models? The post What If I Had AI in 2020: Rent The Runway Dynamic Pricing…
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Where Hurricanes Hit Hardest: A County-Level Analysis with Python
Where Hurricanes Hit Hardest: A County-Level Analysis with Python Use Python, GeoPandas, Tropycal, and Plotly Express to map the number of hurricane encounters per county over the past 50 years. The post Where Hurricanes Hit Hardest: A County-Level Analysis with Python appeared first on Towards Data Science. Lee Vaughan Go to original source
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Designing Trustworthy ML Models: Alan & Aida Discover Monotonicity in Machine Learning
Designing Trustworthy ML Models: Alan & Aida Discover Monotonicity in Machine Learning Accuracy alone doesn’t guarantee trustworthiness. Monotonicity ensures predictions align with common sense and business rules. The post Designing Trustworthy ML Models: Alan & Aida Discover Monotonicity in Machine Learning appeared first on Towards Data Science. Mehdi Mohammadi Go to original source
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Everything You Need to Know About the New Power BI Storage Mode
Everything You Need to Know About the New Power BI Storage Mode 50 Shades of Direct Lake The post Everything You Need to Know About the New Power BI Storage Mode appeared first on Towards Data Science. Nikola Ilic Go to original source
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AI Agents for Supply Chain Optimisation: Production Planning
AI Agents for Supply Chain Optimisation: Production Planning How to integrate an optimisation algorithm in a FastAPI microservice and connect it with an AI workflow to automate production planning. The post AI Agents for Supply Chain Optimisation: Production Planning appeared first on Towards Data Science. Samir Saci Go to original source
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My Most Valuable Lesson as an Aspiring Data Analyst
My Most Valuable Lesson as an Aspiring Data Analyst What my internship taught me about the power of collaboration in data analysis. The post My Most Valuable Lesson as an Aspiring Data Analyst appeared first on Towards Data Science. Benjamin Nweke Go to original source
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Mastering NLP with spaCy – Part 3
Mastering NLP with spaCy – Part 3 Rule-based matching for information extraction The post Mastering NLP with spaCy – Part 3 appeared first on Towards Data Science. Marcello Politi Go to original source
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Help Your Model Learn the True Signal
Help Your Model Learn the True Signal An algorithm-agnostic approach inspired by Cook’s distance The post Help Your Model Learn the True Signal appeared first on Towards Data Science. Mena Wang Go to original source
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Advanced Prompt Engineering for Data Science Projects
Advanced Prompt Engineering for Data Science Projects Part 2: Prompt Engineering for Features, Modeling, and Evaluation The post Advanced Prompt Engineering for Data Science Projects appeared first on Towards Data Science. Sara Nobrega Go to original source
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Modular Arithmetic in Data Science
Modular Arithmetic in Data Science Modular arithmetic is a mathematical system where numbers cycle back to the beginning after reaching a value called the modulus. The system is often referred to as “clock arithmetic” due to its similarity to how analog 12-hour clocks represent time. This article provides a conceptual overview of modular arithmetic and…
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How to Correctly Apply Limits on the Result in DAX (and SQL)
How to Correctly Apply Limits on the Result in DAX (and SQL) What if the output of a measure mustn’t be above a specific limit? How can we ensure that the total is calculated correctly? This piece is about correctly calculating and summarizing such output. The post How to Correctly Apply Limits on the Result…
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How to Use LLMs for Powerful Automatic Evaluations
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. Eivind Kjosbakken Go to original source
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Data Mesh Diaries: Realities from Early Adopters
Data Mesh Diaries: Realities from Early Adopters Early-adopter realities gathered from real data mesh implementations The post Data Mesh Diaries: Realities from Early Adopters appeared first on Towards Data Science. Corné POTGIETER Go to original source
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A Bird’s-Eye View of Linear Algebra: Why Is Matrix Multiplication Like That?
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…
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Reducing Time to Value for Data Science Projects: Part 4
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. Kristopher McGlinchey Go to original source