Tag: what
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What Makes Quantum Machine Learning “Quantum”?
What Makes Quantum Machine Learning “Quantum”? And where is it today? The post What Makes Quantum Machine Learning “Quantum”? appeared first on Towards Data Science. Sara A. Metwalli Go to original source
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What differentiates a high impact analytics function from one that just produces dashboards?
What differentiates a high impact analytics function from one that just produces dashboards? I’m curious to hear from folks who’ve worked inside or alongside analytics teams. In your experience, what actually separates analytics groups that influence business decisions from those that mostly deliver reporting? submitted by /u/Proof_Wrap_2150 [link] [comments] /u/Proof_Wrap_2150 Go to original source
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What I Am Doing to Stay Relevant as a Senior Analytics Consultant in 2026
What I Am Doing to Stay Relevant as a Senior Analytics Consultant in 2026 Learn how to work with AI, while strengthening your unique human skills that technology cannot replace The post What I Am Doing to Stay Relevant as a Senior Analytics Consultant in 2026 appeared first on Towards Data Science. Rashi Desai Go…
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What Other Industries Can Learn from Healthcare’s Knowledge Graphs
What Other Industries Can Learn from Healthcare’s Knowledge Graphs How shared meaning, evidence, and standards create durable semantic infrastructure The post What Other Industries Can Learn from Healthcare’s Knowledge Graphs appeared first on Towards Data Science. Steve Hedden Go to original source
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What Is a Knowledge Graph — and Why It Matters
What Is a Knowledge Graph — and Why It Matters How structured knowledge became healthcare’s quiet advantage The post What Is a Knowledge Graph — and Why It Matters appeared first on Towards Data Science. Steve Hedden Go to original source
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Measuring What Matters with NeMo Agent Toolkit
Measuring What Matters with NeMo Agent Toolkit A practical guide to observability, evaluations, and model comparisons The post Measuring What Matters with NeMo Agent Toolkit appeared first on Towards Data Science. Mariya Mansurova Go to original source
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What Advent of Code Has Taught Me About Data Science
What Advent of Code Has Taught Me About Data Science Five key learnings that I discovered during a programming challenge and how they apply to data science The post What Advent of Code Has Taught Me About Data Science appeared first on Towards Data Science. Jasper Schroeder Go to original source
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What skills did you learn on the job this past year?
What skills did you learn on the job this past year? What skills did you actually learn on the job this past year? Not from self-study or online courses, but through live hands-on training or genuinely challenging assignments. My hunch is that learning opportunities have declined recently, with many companies leaning on “you own your…
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What Building My First Dashboard Taught Me About Data Storytelling
What Building My First Dashboard Taught Me About Data Storytelling Why clarity beats complexity when turning data into stories people actually understand The post What Building My First Dashboard Taught Me About Data Storytelling appeared first on Towards Data Science. Benjamin Nweke Go to original source
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What to Do When Your Credit Risk Model Works Today, but Breaks Six Months Later
What to Do When Your Credit Risk Model Works Today, but Breaks Six Months Later Here’s why it happens — and how to fix it The post What to Do When Your Credit Risk Model Works Today, but Breaks Six Months Later appeared first on Towards Data Science. Javier Marin Go to original source
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Has anyones company successfully implemented what is being described as ACP or an AI Mesh?
Has anyones company successfully implemented what is being described as ACP or an AI Mesh? Has anyones company implemented what is generally described as ACP or what McKinsey describes as an AI Mesh? The concept is a centralized space for AI Agents to “talk to each other”. The link below is a general infographic comparing…
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Water Cooler Small Talk, Ep. 9: What “Thinking” and “Reasoning” Really Mean in AI and LLMs
Water Cooler Small Talk, Ep. 9: What “Thinking” and “Reasoning” Really Mean in AI and LLMs Understanding how AI models “reason” and why it’s not what humans do when we think The post Water Cooler Small Talk, Ep. 9: What “Thinking” and “Reasoning” Really Mean in AI and LLMs appeared first on Towards Data Science.…
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What should I ask my potential managers when choosing between two jobs?
What should I ask my potential managers when choosing between two jobs? I’m deciding between two mid-level data science offers at large tech companies. These are more applied scientist type of roles than analytics. Comp and level are similar, so I’m really trying to figure out which one will set me up for a stronger…
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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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What interesting projects are you working on that are not related to AI?
What interesting projects are you working on that are not related to AI? Share links if possible. submitted by /u/yaymayhun [link] [comments] /u/yaymayhun Go to original source
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What Clients Really Ask for in AI Projects
What Clients Really Ask for in AI Projects Managing AI projects is no walk in the park, but you have the power to make it easier for everyone The post What Clients Really Ask for in AI Projects appeared first on Towards Data Science. Ivo Bernardo Go to original source
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What’s the right thing to say to salary expectations question?
What’s the right thing to say to salary expectations question? I have come across usually two types of scenarios here and I am not sure what’s the best way to deal. I ask for a range and they give you range. Should you just say you’re okay with the range? But what if I make…
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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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What is Universality in LLMs? How to Find Universal Neurons
What is Universality in LLMs? How to Find Universal Neurons How independently trained transformers form same the neurons The post What is Universality in LLMs? How to Find Universal Neurons appeared first on Towards Data Science. Shuyang 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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What Does “Following Best Practices” Mean in the Age of AI?
What Does “Following Best Practices” Mean in the Age of AI? How data and ML practitioners should navigate a rapidly changing landscape The post What Does “Following Best Practices” Mean in the Age of AI? appeared first on Towards Data Science. TDS Editors Go to original source
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What Is Data Literacy in 2025? It’s Not What You Think
What Is Data Literacy in 2025? It’s Not What You Think In today’s fast-paced, distraction-heavy world, data literacy isn’t just about understanding charts or analyzing numbers—it’s about context, clarity, and human connection. With attention spans shrinking and AI-generated insights flooding our screens, even highly skilled professionals can behave like data novices. The real challenge isn’t…
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What Optimization Terminologies for Linear Programming Really Mean
What Optimization Terminologies for Linear Programming Really Mean Understanding the duality of optimization problem, primal to dual conversion, and the optimality conditions for linear problems. The post What Optimization Terminologies for Linear Programming Really Mean appeared first on Towards Data Science. Himalaya Bir Shrestha Go to original source
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What Can the History of Data Tell Us About the Future of AI?
What Can the History of Data Tell Us About the Future of AI? A 40-Year Look at Data, Business Models, and the Forces Shaping Intelligent Systems The post What Can the History of Data Tell Us About the Future of AI? appeared first on Towards Data Science. Steve Hedden Go to original source
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What I Learned in my First 18 Months as a Freelance Data Scientist
What I Learned in my First 18 Months as a Freelance Data Scientist The taxes and health insurance edition The post What I Learned in my First 18 Months as a Freelance Data Scientist appeared first on Towards Data Science. CJ Sullivan Go to original source
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Long-timers at companies — what’s your secret?
Long-timers at companies — what’s your secret? Hi everyone, I’ve been a job hopper throughout my career—never stayed at one place for more than 1-2 years, usually for various reasons. Now, I’m entering a phase where I want to get more settled. I’m about to start a new job and would love to hear from…
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What PyTorch Really Means by a Leaf Tensor and Its Grad
What PyTorch Really Means by a Leaf Tensor and Its Grad The secret life of leaves, gradients, and the mighty requires_grad flag The post What PyTorch Really Means by a Leaf Tensor and Its Grad appeared first on Towards Data Science. Maciej J. Mikulski Go to original source
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What If I had AI in 2018: Rent the Runway Fulfillment Center Optimization
What If I had AI in 2018: Rent the Runway Fulfillment Center Optimization An LLM in 2018 would not have trivialized a complex project, although it could have enhanced the final solution The post What If I had AI in 2018: Rent the Runway Fulfillment Center Optimization appeared first on Towards Data Science. Hugo Ducruc…
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What is your domain and what are the most important technical skills that help you stand out in your domain?
What is your domain and what are the most important technical skills that help you stand out in your domain? Aside from soft skills and domain expertise, ofc those are a given. I’m manufacturing-adjacent (closer to product development and validation). Design of experiments has been my most useful data-related skill. I’m always being asked “We…
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What is your functional area?
What is your functional area? I don’t mean industry. I mean product, operations, etc. I work in operations. I don’t grow the business. I keep the business alive. submitted by /u/Trick-Interaction396 [link] [comments] /u/Trick-Interaction396 Go to original source
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What Statistics Can Tell Us About NBA Coaches
What Statistics Can Tell Us About NBA Coaches Using Python to determine where NBA coaches come from and what makes them successful The post What Statistics Can Tell Us About NBA Coaches appeared first on Towards Data Science. Brayden Gerrard Go to original source
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Non-Parametric Density Estimation: Theory and Applications
Non-Parametric Density Estimation: Theory and Applications In this article, we’ll talk about what Density Estimation is and the role it plays in statistical analysis. We’ll analyze two popular density estimation methods, histograms and kernel density estimators, and analyze their theoretical properties as well as how they perform in practice. Finally, we’ll look at how density…
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How I Finally Understood MCP — and Got It Working in Real Life
How I Finally Understood MCP — and Got It Working in Real Life Table of Content Introduction: Why I Wrote This The Evolution of Tool Integration with LLMs What Is Model Context Protocol (MCP), Really? Wait, MCP sounds like RAG… but is it? In an MCP-based setup In a traditional RAG system Traditional RAG Implementation MCP Implementation…
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Beyond Glorified Curve Fitting: Exploring the Probabilistic Foundations of Machine Learning
Beyond Glorified Curve Fitting: Exploring the Probabilistic Foundations of Machine Learning You see a math formula you don’t immediately understand. Your instinct? Stop reading. Don’t. That’s exactly what I told myself when I started reading Probabilistic Machine Learning – An Introduction by Kevin P. Murphy. And it was absolutely worth it. It changed how I…
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Predicting the NBA Champion with Machine Learning
Predicting the NBA Champion with Machine Learning Every NBA season, 30 teams compete for something only one will achieve: the legacy of a championship. From power rankings to trade deadline chaos and injuries, fans and analysts alike speculate endlessly about who will raise the Larry O’Brien Trophy. But what if we could go beyond the hot…
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Japanese-Chinese Translation with GenAI: What Works and What Doesn’t
Japanese-Chinese Translation with GenAI: What Works and What Doesn’t Authors Alex (Qian) Wan: Alex (Qian) is a designer specializing in AI for B2B products. She is currently working at Microsoft, focusing on machine learning and Copilot for data analysis. Previously, she was the Gen AI design lead at VMware.Eli Ruoyong Hong : Eli is a…
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The Cultural Backlash Against Generative AI
The Cultural Backlash Against Generative AI What’s making many people resent generative AI, and what impact does that have on the companies responsible? Photo by Joshua Hoehne on Unsplash The recent reveal of DeepSeek-R1, the large scale LLM developed by a Chinese company (also named DeepSeek), has been a very interesting event for those of us…
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What is MicroPython? Do I Need to Know it as a Data Scientist?
What is MicroPython? Do I Need to Know it as a Data Scientist? In this year’s edition of the Stack Overflow survey, MicroPython is with 1.6% in the Most Popular Technologies — but why? Continue reading on Towards Data Science » Sarah Lea Go to original source
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What Would a Stoic Do? — An AI-Based Decision-Making Model
What Would a Stoic Do? — An AI-Based Decision-Making Model Using AI to build Marcus Aurelius’ reincarnation Continue reading on Towards Data Science » Pol Marin Go to original source
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What to Do If the Logit Decision Boundary Fails?
What to Do If the Logit Decision Boundary Fails? Feature engineering for classification models using Bayesian Machine Learning Continue reading on Towards Data Science » Lukasz Gatarek Go to original source
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What’s your biggest time sink as a data scientist?
What’s your biggest time sink as a data scientist? I’ve got a few ideas for DS tooling I was thinking of taking on as a side project, so this is a bit of a market research post. I’m curious what data-scientist specific task/problem is the biggest time suck for you at work. I feel like…
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What I’m Updating in My AI Ethics Class for 2025
What I’m Updating in My AI Ethics Class for 2025 What happened in 2024 that is new and significant in the world of AI ethics? The new technology developments have come in fast, but what has ethical or values implications that are going to matter long-term? I’ve been working on updates for my 2025 class…
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What Every Aspiring Machine Learning Engineer Must Know to Succeed
What Every Aspiring Machine Learning Engineer Must Know to Succeed Your Guide to Avoiding Critical Errors with Machine Learning in Production Continue reading on Towards Data Science » Claudia Ng Go to original source
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What projects are you working on and what is the benefit of your efforts?
What projects are you working on and what is the benefit of your efforts? I would really like to hear what you guys are working on, challenges you’re facing and how your project is helping your company. Let’s hear it. submitted by /u/Firm-Message-2971 [link] [comments] /u/Firm-Message-2971 Go to original source
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What’s the point of testing machine learning model knowledge during interviews for non-research data science roles?
What’s the point of testing machine learning model knowledge during interviews for non-research data science roles? I always make an effort to learn how a model works and how it differs from other similar models whenever I encounter a new model. So it felt natural to me that these topics were brought up in interviews.…
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Here’s What I Learned About Information Theory Through Wordle
Here’s What I Learned About Information Theory Through Wordle The Science Behind Better Guesses Continue reading on Towards Data Science » Saankhya Mondal Go to original source
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what am i going to do with this?
https://github.com/ictnlp/Auto-RAG or this? https://vast.ai/docs/use-cases/oobabooga https://alexfazio.medium.com/a-brief-intro-to-obabooga-text-generation-webui-711f783cae48
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Who Does What in Data? A Practical Introduction to the Role of a Data Engineer & Data Scientist
Who Does What in Data? A Practical Introduction to the Role of a Data Engineer & Data Scientist What does a data engineer do differently to a data scientist? Continue reading on Towards Data Science » Sarah Lea Go to original source
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What’s going on everybody?
What’s going on everybody? sentdex Go to original source
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what will the intern do now?
https://github.com/DocumindHQ/documind oh they’re the same? https://github.com/getomni-ai/zerox oh another one! https://github.com/DS4SD/docling/ and this! https://github.com/clovaai/donut and this!! https://github.com/Zipstack/unstract does this count? https://anythingllm.com/