Category: data-science
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How to Evaluate LLM Summarization
How to Evaluate LLM Summarization A practical and effective guide for evaluating AI summaries Image from Unsplash Summarization is one of the most practical and convenient tasks enabled by LLMs. However, compared to other LLM tasks like question-asking or classification, evaluating LLMs on summarization is far more challenging. And so I myself have neglected evals for…
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LyRec: A Song Recommender That Reads Between the Lyrics
LyRec: A Song Recommender That Reads Between the Lyrics This is how I built an emotionally intelligent LLM-powered song recommendation system. Photo by David Pupăză on Unsplash Do you remember the last time you found yourself obsessing over a song? Maybe it was the raw emotion that resonated with you, or perhaps it was the lyrics…
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Building a Data Dashboard
Building a Data Dashboard Using the streamlit Python library Continue reading on Towards Data Science » Thomas Reid Go to original source
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The Concepts Data Professionals Should Know in 2025: Part 1
The Concepts Data Professionals Should Know in 2025: Part 1 From Data Lakehouses to Event-Driven Architecture — Master 12 data concepts and turn them into simple projects to stay ahead in IT. Continue reading on Towards Data Science » Sarah Lea Go to original source
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How to Log Your Data with MLflow
How to Log Your Data with MLflow MLflow, MLOps, Data Science Mastering data logging in MLOps for your AI workflow Photo by Chris Liverani on Unsplash Preface Data is one of the most critical components of the machine learning process. In fact, the quality of the data used in training a model often determines the success or failure…
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Satellite Image Classification with Deep Learning — Complete Project
Satellite Image Classification with Deep Learning — Complete Project A Comprehensive Guide Using PyTorch and CNNs Continue reading on Towards Data Science » Leo Anello Go to original source
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Where to Start When Data is Limited
Where to Start When Data is Limited A launch pad for projects with small datasets Photo by Google DeepMind: https://www.pexels.com/photo/an-artist-s-illustration-of-artificial-intelligence-ai-this-image-depicts-how-ai-can-help-humans-to-understand-the-complexity-of-biology-it-was-created-by-artist-khyati-trehan-as-part-17484975/ Machine Learning (ML) has driven remarkable breakthroughs in computer vision, natural language processing, and speech recognition, largely due to the abundance of data in these fields. However, many challenges — especially those tied to specific product features or…
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Learning from Machine Learning | Sebastian Raschka: Mastering ML and Pushing AI Forward Responsibly
Learning from Machine Learning | Sebastian Raschka: Mastering ML and Pushing AI Forward Responsibly Sebastian Raschka has helped demystify deep learning for thousands through his books, tutorials and teachings Sebastian Raschka has helped shape how thousands of data scientists and machine learning engineers learn their craft. As a passionate coder and proponent of open-source software,…
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A Practical Exploration of Sora — Intuitively and Exhaustively Explained
A Practical Exploration of Sora — Intuitively and Exhaustively Explained A new cutting edge video generation tool, and the theory behind it Continue reading on Towards Data Science » Daniel Warfield Go to original source
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Learnings from a Machine Learning Engineer — Part 2: The Data Sets
Learnings from a Machine Learning Engineer — Part 2: The Data Sets Practical insights for a data-driven approach to model optimization Continue reading on Towards Data Science » David Martin Go to original source
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Top 3 Questions to Ask in Near Real-Time Data Solutions
Top 3 Questions to Ask in Near Real-Time Data Solutions Questions that guide architectural decisions to balance functional requirements with non-functional ones, like latency and scalability Continue reading on Towards Data Science » Shawn Shi Go to original source
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The Data Analyst Every CEO Wants
The Data Analyst Every CEO Wants Data Analyst is probably the most underrated job in the data industry Continue reading on Towards Data Science » Benoit Pimpaud Go to original source
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Basics of GANs & SMOTE for Data Augmentation
Basics of GANs & SMOTE for Data Augmentation GANs and SMOTE Explained with Bartending: Data Science for Machine Learning Series (1) Continue reading on Towards Data Science » Sunghyun Ahn Go to original source
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Learnings from a Machine Learning Engineer — Part 1: The Data
Learnings from a Machine Learning Engineer — Part 1: The Data Practical insights for a data-driven approach to model optimization Continue reading on Towards Data Science » David Martin Go to original source
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Water Cooler Small Talk: Benford’s Law
Water Cooler Small Talk: Benford’s Law A look into the strange first digit distribution of naturally occurring datasets Continue reading on Towards Data Science » Maria Mouschoutzi, PhD Go to original source
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Hands-On Delivery Routes Optimization (TSP) with AI, Using LKH and Python
Hands-On Delivery Routes Optimization (TSP) with AI, Using LKH and Python Here’s how to optimize the delivery routes, from theory to code. Continue reading on Towards Data Science » Piero Paialunga Go to original source
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How To: Forecast Time Series Using Lags
How To: Forecast Time Series Using Lags Lag columns can significantly boost your model’s performance Continue reading on Towards Data Science » Haden Pelletier Go to original source
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Scale Experiment Decision-Making with Programmatic Decision Rules
Scale Experiment Decision-Making with Programmatic Decision Rules Decide what to do with experiment results in code Photo by Cytonn Photography on Unsplash The experiment lifecycle is like the human lifecycle. First, a person or idea is born, then it develops, then it is tested, then its test ends, and then the Gods (or Product Managers) decide its worth.…
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Four Ways to Improve Statistical Power in A/B Testing (Without Increasing Test Duration, Duh)
Four Ways to Improve Statistical Power in A/B Testing (Without Increasing Test Duration, Duh) In A/B testing, you often have to balance statistical power and how long the test takes. Learn how Allocation, Effect Size, CUPED & Binarization can help you. Image by author In A/B testing, you often have to balance statistical power and how long…
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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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Your Classifier Is Broken, But It Is Still Useful
Your Classifier Is Broken, But It Is Still Useful When you run a binary classifier over a population you get an estimate of the proportion of true positives in that population. This is known as the prevalence. Photo by Rod Long on Unsplash But that estimate is biased, because no classifier is perfect. For example, if…
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LightGBM: The Fastest Option of Gradient Boosting
LightGBM: The Fastest Option of Gradient Boosting Learn how to implement a fast and effective Gradient Boosting model using Python Continue reading on Towards Data Science » Gustavo R Santos Go to original source
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3 Powerful Examples of the Python Re Library
3 Powerful Examples of the Python Re Library Explore the power of regex and save time in data analysis Continue reading on Towards Data Science » Suraj Gurav Go to original source
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Solving A Rubik’s Cube with Supervised Learning — Intuitively and Exhaustively Explained
Solving A Rubik’s Cube with Supervised Learning — Intuitively and Exhaustively Explained A Popular Toy in a Brave New World Continue reading on Towards Data Science » Daniel Warfield Go to original source
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Sustainable Business Strategy with Data Analytics
Sustainable Business Strategy with Data Analytics Use data analytics to help companies design and implement strategic sustainability roadmaps to reduce their environmental footprint. Sustainable Business Strategy with Analytics — (Image by Samir Saci) Consensus means that everyone agrees to say collectively what no one believes individually. This quote captures a critical issue many companies face during their strategic…
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The Best Way to Prepare for Data Science and Machine Learning Interviews
The Best Way to Prepare for Data Science and Machine Learning Interviews Never get stumped again Continue reading on Towards Data Science » Marina Wyss – Gratitude Driven Go to original source
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Sentiment Analysis with Transformers: A Complete Deep Learning Project — PT. I
Sentiment Analysis with Transformers: A Complete Deep Learning Project — PT. I Master Fine-Tuning Transformers, Comparing Deep Learning Architectures, and Deploying Sentiment Analysis Models Continue reading on Towards Data Science » Leo Anello Go to original source
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How to Run Jupyter Notebooks and Generate HTML Reports with Python Scripts
How to Run Jupyter Notebooks and Generate HTML Reports with Python Scripts A step-by-step guide to automating Jupyter Notebook execution and report generation using Python Continue reading on Towards Data Science » Amanda Iglesias Moreno Go to original source
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Advanced SQL Techniques for Unstructured Data Handling
Advanced SQL Techniques for Unstructured Data Handling Everything you need to know to get started with text mining Continue reading on Towards Data Science » Jiayan Yin Go to original source
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Bayesian A/B Testing Falls Short
Bayesian A/B Testing Falls Short Why Bayesian A/B testing can lead to misunderstandings, inflated false positive rates, introduce bias and complicate results (Image generated by the author using Midjourney) Over the past decade, I’ve engaged in countless discussions about Bayesian A/B testing versus Frequentist A/B testing. In nearly every conversation, I’ve maintained the same viewpoint:…
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Method of Moments Estimation with Python Code
Method of Moments Estimation with Python Code How to understand and implement the estimator from scratch Photo by Petr Macháček on Unsplash Let’s say you are in a customer care center, and you would like to know the probability distribution of the number of calls per minute, or in other words, you want to answer the question:…
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Encapsulation: A Software Engineering Concept Data Scientists Must Know To Succeed
Encapsulation: A Software Engineering Concept Data Scientists Must Know To Succeed Simple concepts that differentiate a professional from amateurs Continue reading on Towards Data Science » Benjamin Lee Go to original source
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In Defense of Statistical Significance
In Defense of Statistical Significance We have to draw the line somewhere Photo by Siora Photography on Unsplash It’s become something of a meme that statistical significance is a bad standard. Several recent blogs have made the rounds, making the case that statistical significance is a “cult” or “arbitrary.” If you’d like a classic polemic (and…
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Data behind the Luck, Ambition, and a Billion-Dollar Dream: Lottery
Data behind the Luck, Ambition, and a Billion-Dollar Dream: Lottery Using Seattle’s local retail store data for consumer patterns of the lottery (SQL, Python) Continue reading on Towards Data Science » Sunghyun Ahn Go to original source
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Predicting a Ball Trajectory
Predicting a Ball Trajectory Polynomial Fit in Python with NumPy Continue reading on Towards Data Science » Florian Trautweiler Go to original source
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Mastering the Basics: How Linear Regression Unlocks the Secrets of Complex Models
Mastering the Basics: How Linear Regression Unlocks the Secrets of Complex Models Full explanation on Linear Regression and how it learns The Crane Stance. Public Domain image from Openverse Just like Mr. Miyagi taught young Daniel LaRusso karate through repetitive simple chores, which ultimately transformed him into the Karate Kid, mastering foundational algorithms like linear regression…
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Journey to Full-Stack Data Scientist: Model Deployment
Journey to Full-Stack Data Scientist: Model Deployment An introduction to productionizing machine learning models using APIs and Docker. Growing Responsibilities of Data Scientists The title of data scientist is ever-changing and often vague. It usually involves one who is fluent in mathematics, programming, and machine learning. They spend time cleaning data, building models, fine-tuning, and conducting…
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The Next Frontier in LLM Accuracy
The Next Frontier in LLM Accuracy Exploring the Power of Lamini Memory Tuning Image generated by DALL-E 3 Accuracy is often critical for LLM applications, especially in cases such as API calling or summarisation of financial reports. Fortunately, there are ways to enhance precision. The best practices to improve accuracy include the following steps: You can start…
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How to Tell Among Two Regression Models with Statistical Significance
How to Tell Among Two Regression Models with Statistical Significance Diving into the F-test for nested models with algorithms, examples and code Continue reading on Towards Data Science » LucianoSphere (Luciano Abriata, PhD) Go to original source
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Chi-Squared Test: Comparing Variations Through Soccer
Chi-Squared Test: Comparing Variations Through Soccer Understanding Different Types of Chi-Squared Tests: A/B Testing for Data Science Series (8) Continue reading on Towards Data Science » Sunghyun Ahn Go to original source
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Non-Technical Principles All Data Scientists Should Have
Non-Technical Principles All Data Scientists Should Have Making you a better data scientist, and enhancing your career. Continue reading on Towards Data Science » Marc Matterson Go to original source
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How to Stand Out in The Data Science Job Market
How to Stand Out in The Data Science Job Market How to have the edge in your data science application Continue reading on Towards Data Science » Egor Howell Go to original source
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Scaling Statistics: Incremental Standard Deviation in SQL with dbt
Scaling Statistics: Incremental Standard Deviation in SQL with dbt Why scan yesterday’s data when you can increment today’s? Image by the author SQL aggregation functions can be computationally expensive when applied to large datasets. As datasets grow, recalculating metrics over the entire dataset repeatedly becomes inefficient. To address this challenge, incremental aggregation is often employed — a method…
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Stop the Count! Why Putting A Time Limit on Metrics is Critical for Fast and Accurate Experiments
Stop the Count! Why Putting A Time Limit on Metrics is Critical for Fast and Accurate Experiments Why your experiments might never reach significance Photo by Andrik Langfield on Unsplash Introduction Experiments usually compare the frequency of an event (or some other sum metric) after either exposure (treatment) or non-exposure (control) to some intervention. For example:…
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Top 12 Skills Data Scientists Need to Succeed in 2025
Top 12 Skills Data Scientists Need to Succeed in 2025 It’s (not) all about LLMs and AI tools Continue reading on Towards Data Science » Benjamin Bodner Go to original source
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Creating SMOTE Oversampling from Scratch
Creating SMOTE Oversampling from Scratch A Python tutorial on how to implement oversampling and how to make custom variations Continue reading on Towards Data Science » Hari Devanathan Go to original source
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Lessons from COVID-19: Why Probability Distributions Matter
Lessons from COVID-19: Why Probability Distributions Matter Understanding Distributions with Extremes: Probability for Data Science Series (END) Continue reading on Towards Data Science » Sunghyun Ahn Go to original source
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How to Ensure the Stability of a Model Using Jackknife Estimation
How to Ensure the Stability of a Model Using Jackknife Estimation How to ensure the robustness of a model and detect influential data observations Continue reading on Towards Data Science » Paula LC Go to original source
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Mastering Model Uncertainty: Thresholding Techniques in Deep Learning
Mastering Model Uncertainty: Thresholding Techniques in Deep Learning Image generated by Dall-e A few words on thresholding, the softmax activation function, introducing an extra label, and considerations regarding output activation functions. In many real-world applications, machine learning models are not designed to make decisions in an all-or-nothing manner. Instead, there are situations where it is more…
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How To Start A Data Science Blog on Medium
How To Start A Data Science Blog on Medium Tips on how to get started, write your first article, and get noticed Continue reading on Towards Data Science » Haden Pelletier Go to original source
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Understanding When and How to Implement FastAPI Middleware (Examples and Use Cases)
Understanding When and How to Implement FastAPI Middleware (Examples and Use Cases) Supercharge Your FastAPI with Middleware: Practical Use Cases and Examples Continue reading on Towards Data Science » Mike Huls Go to original source
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Three Important Pandas Functions You Need to Know
Three Important Pandas Functions You Need to Know Master these techniques to stand out as a Python developer Continue reading on Towards Data Science » Jiayan Yin Go to original source
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Probability Distributions: Poisson vs. Binomial Distribution
Probability Distributions: Poisson vs. Binomial Distribution Using Soccer to Understand the Difference Between Poisson & Binomial: Probability for Data Science Series (3) Continue reading on Towards Data Science » Sunghyun Ahn Go to original source
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A Bird’s-Eye View of Linear Algebra: Orthonormal Matrices
A Bird’s-Eye View of Linear Algebra: Orthonormal Matrices Orthonormal matrices: the most elegant matrices in all of linear algebra. Continue reading on Towards Data Science » Rohit Pandey Go to original source
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I’m Doing the Advent of Code 2024 in Python — Day 4
I’m Doing the Advent of Code 2024 in Python — Day 4 Let’s see how many stars we’ll collect. Continue reading on Towards Data Science » Soner Yıldırım Go to original source
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How to Clean Your Data for Your Real-Life Data Science Projects
How to Clean Your Data for Your Real-Life Data Science Projects How I treat missing values—with a quick Python Guide Continue reading on Towards Data Science » Mythili Krishnan Go to original source
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Adapted Prediction Intervals by Means of Conformal Predictions and a Custom Non-Conformity Score
Adapted Prediction Intervals by Means of Conformal Predictions and a Custom Non-Conformity Score How confident should I be in a machine learning model’s prediction for a new data point? Could I get a range of likely values? Image by author When working on a supervised task, machine learning models can be used to predict the outcome for…
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How (and Where) ML Beginners Can Find Papers
How (and Where) ML Beginners Can Find Papers From conferences to surveys Continue reading on Towards Data Science » Pascal Janetzky Go to original source
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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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Propensity-Score Matching Is the Bedrock of Causal Inference
Propensity-Score Matching Is the Bedrock of Causal Inference And how to get started with it using Python Continue reading on Towards Data Science » Ari Joury, PhD Go to original source
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When Averages Lie: Moving Beyond Single-Point Predictions
When Averages Lie: Moving Beyond Single-Point Predictions The Case for Predicting Full Probability Distributions in Decision-Making Some people like hot coffee, some people like iced coffee, but no one likes lukewarm coffee. Yet, a simple model trained on coffee temperatures might predict that the next coffee served should be… lukewarm. This illustrates a fundamental problem…
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Ranking Basics: Pointwise, Pairwise, Listwise
Ranking Basics: Pointwise, Pairwise, Listwise Because thy neighbour matters Image taken from unsplash.com First, let’s talk about where ranking comes into play. Ranking is a big deal in e-commerce and search applications — essentially, any scenario where you need to organize documents based on a query. It’s a little different from classic classification or regression problems. For…
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Understanding Deduplication Methods: Ways to Preserve the Integrity of Your Data
Understanding Deduplication Methods: Ways to Preserve the Integrity of Your Data Increasing growth and data complexities have made data deduplication even more relevant Data duplication is still a problem for many organisations. Although data processing and storage systems have developed rapidly along with technological advances, the complexity of the data produced is also increasing. Moreover, with…
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How to Stand Out as a Junior Data Scientist
How to Stand Out as a Junior Data Scientist 7 things you can do to show your skills even if you have no experience at all Continue reading on Towards Data Science » Idit Cohen Go to original source
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From Prototype to Production: Enhancing LLM Accuracy
From Prototype to Production: Enhancing LLM Accuracy Implementing evaluation frameworks to optimize accuracy in real-world applications Image created by DALL-E 3 Building a prototype for an LLM application is surprisingly straightforward. You can often create a functional first version within just a few hours. This initial prototype will likely provide results that look legitimate and be…
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Synthetic Control Sample for Before and After A/B Test
Synthetic Control Sample for Before and After A/B Test Learn a simple way to use linear regression to create a synthetic control sample for your A/B test Continue reading on Towards Data Science » Gustavo R Santos Go to original source
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2024 Highlights: The AI and Data Science Articles That Made a Splash
2024 Highlights: The AI and Data Science Articles That Made a Splash Feeling inspired to write your first TDS post before the end of 2024? We’re always open to contributions from new authors. And just like that, 2024 is (almost) in the books. It was a year of exciting transitions — both for the TDS team and, in…
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2024 in Review: What I Got Right, Where I Was Wrong, and Bolder Predictions for 2025
2024 in Review: What I Got Right, Where I Was Wrong, and Bolder Predictions for 2025 What I got right (and wrong) about trends in 2024 and daring to make bolder predictions for the year ahead AI Buzzword and Trend Bingo (Image by the author) In 2023, building AI-powered applications felt full of promise, but the challenges…
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Four Career-Savers Data Scientists Should Incorporate into Their Work
Four Career-Savers Data Scientists Should Incorporate into Their Work You might damage your data science career progress without even realising it — but avoiding that fate isn’t too difficult Continue reading on Towards Data Science » Egor Howell Go to original source
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Four Signs It’s Time to Leave Your Data Science Job
Four Signs It’s Time to Leave Your Data Science Job Four tell-tale signs that you should look for another job Continue reading on Towards Data Science » Egor Howell Go to original source
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A Case for Bagging and Boosting as Data Scientists’ Best Friends
A Case for Bagging and Boosting as Data Scientists’ Best Friends Leveraging wisdom of the crowd in ML models. Continue reading on Towards Data Science » Farzad Nobar Go to original source
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The Good, the Bad, An Ugly Memory for a Neural Network
The Good, the Bad, An Ugly Memory for a Neural Network Memory can play tricks, to learn best it is not always good to memorize Continue reading on Towards Data Science » Salvatore Raieli Go to original source
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Structured LLM Output Using Ollama
Structured LLM Output Using Ollama Control your model responses effectively Continue reading on Towards Data Science » Thomas Reid Go to original source
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Credit Card Fraud Detection with Different Sampling Techniques
Credit Card Fraud Detection with Different Sampling Techniques How to deal with imbalanced data Photo by Bermix Studio on Unsplash Credit card fraud detection is a plague that all financial institutions are at risk with. In general fraud detection is very challenging because fraudsters are coming up with new and innovative ways of detecting fraud, so…
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Bayes’ Theorem: Understanding business outcomes with evidence
Bayes’ Theorem: Understanding business outcomes with evidence A practical introduction to Bayes’ Theorem: Probability for Data Science Series (2) Continue reading on Towards Data Science » Sunghyun Ahn Go to original source
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Data Valuation — A Concise Overview
Data Valuation — A Concise Overview Understanding the Value of your Data: Challenges, Methods, and Applications ChatGPT and similar LLMs were trained on insane amounts of data. OpenAI and Co. scraped the internet, collecting books, articles, and social media posts to train their models. It’s easy to imagine that some of the texts (like scientific or news…
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How Have Data Science Interviews Changed Over 4 Years?
How Have Data Science Interviews Changed Over 4 Years? An aggregated look on the differences between then & now: 2020 vs 2024 — some big frustrations and positive learnings. Continue reading on Towards Data Science » Matt Przybyla Go to original source
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Master Machine Learning: 4 Classification Models Made Simple
Master Machine Learning: 4 Classification Models Made Simple A Beginner’s Guide to Building Models in 15 Practical Steps Continue reading on Towards Data Science » Leo Anello Go to original source
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Is Complex Writing Nothing But Formulas?
Is Complex Writing Nothing But Formulas? Text analytics hints at how volumes of writing get created In the broadest of strokes, Natural Language Processing transforms language into constructs that can be usefully manipulated. Since deep-learning embeddings have proven so powerful, they’ve also become the default: pick a model, embed your data, pick a metric, do some…
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Agentic AI: Building Autonomous Systems from Scratch
Agentic AI: Building Autonomous Systems from Scratch A Step-by-Step Guide to Creating Multi-Agent Frameworks in the Age of Generative AI Continue reading on Towards Data Science » Luís Roque Go to original source
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Transformers Key-Value (KV) Caching Explained
Transformers Key-Value (KV) Caching Explained Speed up your LLM inference Continue reading on Towards Data Science » Michał Oleszak Go to original source
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Sentiment analysis template: A complete data science project
Sentiment analysis template: A complete data science project 10 essential steps, from data exploration to model deployment. Continue reading on Towards Data Science » Leo Anello Go to original source
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3 Business Skills You Need to Progress Your Data Science Career in 2025
3 Business Skills You Need to Progress Your Data Science Career in 2025 DATA SCIENCE Including resources for how to build those skills Image by Author. Created using Midjourney If you have been a data scientist for a while, sooner or later you’ll notice that your day-to-day has shifted from a VSCode-loving, research paper-reading, git-version-committing data…
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Translating a Memoir: A Technical Journey
Translating a Memoir: A Technical Journey Leveraging GPT-3.5 and unstructured APIs for translations This blog post details how I utilised GPT to translate the personal memoir of a family friend, making it accessible to a broader audience. Specifically, I employed GPT-3.5 for translation and Unstructured’s APIs for efficient content extraction and formatting. The memoir, a…
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5 Essential Tips to Build Business Dashboards Stakeholders Love
5 Essential Tips to Build Business Dashboards Stakeholders Love A practical guide to designing clear, effective, and actionable dashboards for decision-making Continue reading on Towards Data Science » Yu Dong Go to original source
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I’m Doing the Advent of Code 2024 in Python — Day 2
I’m Doing the Advent of Code 2024 in Python — Day 2 Let’s see how many stars we’ll collect. Continue reading on Towards Data Science » Soner Yıldırım Go to original source
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Awesome Plotly with Code Series (Part 5): The Order in Bar Charts Matters
Awesome Plotly with Code Series (Part 5): The Order in Bar Charts Matters And it is not always simply ordering by highest to lowest Continue reading on Towards Data Science » Jose Parreño Go to original source
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Uncertainty Quantification in Time Series Forecasting
Uncertainty Quantification in Time Series Forecasting A deep dive into EnbPI, a Conformal Prediction approach for time series forecasting Continue reading on Towards Data Science » Jonte Dancker Go to original source
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How to Evaluate Multilingual LLMs With Global-MMLU
How to Evaluate Multilingual LLMs With Global-MMLU Evaluation of language-specific LLM accuracy on the global Massive Multitask Language Understanding benchmark in Python Continue reading on Towards Data Science » Dr. Leon Eversberg Go to original source
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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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Why Data Scientists Need These Software Engineering Skills
Why Data Scientists Need These Software Engineering Skills Learn these things to become a more well-rounded data scientist Continue reading on Towards Data Science » Egor Howell Go to original source
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Streamline Your Workflow when Starting a New Research Paper
Streamline Your Workflow when Starting a New Research Paper Python code to create folders and Word documents for research papers in biomedical sciences — all in one go with only two inputs Continue reading on Towards Data Science » Rodrigo M Carrillo Larco, MD, PhD Go to original source
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AI, My Holiday Elf: Building a Gift Recommender for the Perfect Christmas
AI, My Holiday Elf: Building a Gift Recommender for the Perfect Christmas How I used AI and Streamlit to create a festive and fun gift recommendation app Continue reading on Towards Data Science » Shuqing Ke Go to original source
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How to Prepare for Your Data Science Behavioural Interview
How to Prepare for Your Data Science Behavioural Interview My top tips to smash your next data science behavioural interview Continue reading on Towards Data Science » Egor Howell Go to original source
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I’m Doing the Advent of Code 2024 in Python — Day 1
I’m Doing the Advent of Code 2024 in Python — Day 1 Let’s see how many stars we’ll collect. Continue reading on Towards Data Science » Soner Yıldırım Go to original source
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Combining Large and Small LLMs to Boost Inference Time and Quality
Combining Large and Small LLMs to Boost Inference Time and Quality Implementing Speculative and Contrastive Decoding Large Language models are comprised of billions of parameters (weights). For each word it generates, the model has to perform computationally expensive calculations across all of these parameters. Large Language models accept a sentence, or sequence of tokens, and…
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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 Teaching AI Taught me About Data Skills & People
What Teaching AI Taught me About Data Skills & People Three key lessons from my journey as a corporate AI educator Photo by Mikhail Nilov. As an AI Educator, my job was to equip corporate teams with the data & AI skills they needed to thrive. But looking back, I realized that I learned far more from…