Tag: data
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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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Missing Data in Time-Series: Machine Learning Techniques
Missing Data in Time-Series: Machine Learning Techniques Part 1: Leverage linear regression and decision trees to impute time-series gaps. Continue reading on Towards Data Science » Sara Nóbrega Go to original source
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How to Apply the Central Limit Theorem to Constrained Data
How to Apply the Central Limit Theorem to Constrained Data What can we say about the mean of data distributed in an interval [a, b]? Continue reading on Towards Data Science » Ryan Burn 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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Is your org treating the rollout of LLMs as an IT or data science problem?
Is your org treating the rollout of LLMs as an IT or data science problem? Our org has given all resource (and limited all API access) to LLMs to a dedicated team in the IT department, which has no prior data experience. So far no data scientist has been engaged for feedback on design or…
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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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Bridging the Data Literacy Gap
Bridging the Data Literacy Gap The Advent, Evolution, and Current state of “Data Translators” Introduction With Data being constantly glorified as the most valuable asset organizations can own, leaders and decision-makers are always looking for effective ways to put their data insights to use. Every time customers interact with digital products, millions of data points…
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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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GPS Interpolation Using Maps and Kinematics
GPS Interpolation Using Maps and Kinematics How do you apply dead reckoning to your geospatial dataset? The picture above illustrates the GPS interpolation process. The red dots represent the known and repeated GPS locations, with more than one location per dot, while the blue dots represent the inferred locations of the repeated points along the…
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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…
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Becoming a Data Scientist: What I Would Do If I Had to Start Over
Becoming a Data Scientist: What I Would Do If I Had to Start Over Breaking into data science: The Good, the Bad, and the Python Bugs Photo by Markus Spiske on Unsplash Martin Luther King Jr. is famous for his speech, “I Have a Dream.” He delivered it at the Lincoln Memorial in Washington, D.C., on August…
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Explicit and data-Efficient Encoding via Gradient Flow
Explicit and data-Efficient Encoding via Gradient Flow arXiv:2412.00864v1 Announce Type: new Abstract: The autoencoder model typically uses an encoder to map data to a lower dimensional latent space and a decoder to reconstruct it. However, relying on an encoder for inversion can lead to suboptimal representations, particularly limiting in physical sciences where precision is key.…
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Energy-Based Modelling for Discrete and Mixed Data via Heat Equations on Structured Spaces
Energy-Based Modelling for Discrete and Mixed Data via Heat Equations on Structured Spaces arXiv:2412.01019v1 Announce Type: new Abstract: Energy-based models (EBMs) offer a flexible framework for probabilistic modelling across various data domains. However, training EBMs on data in discrete or mixed state spaces poses significant challenges due to the lack of robust and fast sampling…
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Context-Aided Forecasting: Enhancing Forecasting with Textual Data
Context-Aided Forecasting: Enhancing Forecasting with Textual Data A promising alternative approach to improve forecasting Continue reading on Towards Data Science » Nikos Kafritsas Go to original source
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Need help gathering data
Need help gathering data Hello! I’m currently analysing data from politicians across the world and I would like to know if there’s a database with data like years in charge, studies they had, age, gender and some other relevant topics. Please, if you had any links I’ll be glad to check them all. *Need help,…
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The Lead, Shadow, and Sparring Roles in New Data Settings
The Lead, Shadow, and Sparring Roles in New Data Settings From data engineer to domain expert—what it takes to build a new data platform Continue reading on Towards Data Science » Marina Tosic Go to original source
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Effortless Data Handling: Find Variables Across Multiple Data Files with R
Effortless Data Handling: Find Variables Across Multiple Data Files with R A practical solution with code and workflow Lost in a maze of datasets and endless data dictionaries? Say goodbye to tedious variable hunting! Discover how to quickly identify and extract the variables you need from multiple SAS files using two simple R functions. Streamline your…
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Think you Know Excel? Take Your Analytics Skills to the Next Level with Power Query!
Think you Know Excel? Take Your Analytics Skills to the Next Level with Power Query! 5 practical use cases that prove Power Query is worth exploring. I have a confession to make: I’ve been living under a rock 🪨. Not literally, but how else can I explain not discovering Power Query in Excel until now? Imagine…
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The Most Expensive Data Science Mistake I’ve Witnessed in My Career
The Most Expensive Data Science Mistake I’ve Witnessed in My Career Why true success in machine learning goes beyond optimizing a single metric Continue reading on Towards Data Science » Claudia Ng Go to original source
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Functional relevance based on the continuous Shapley value
Functional relevance based on the continuous Shapley value arXiv:2411.18575v1 Announce Type: new Abstract: The presence of Artificial Intelligence (AI) in our society is increasing, which brings with it the need to understand the behaviour of AI mechanisms, including machine learning predictive algorithms fed with tabular data, text, or images, among other types of data. This…
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How to Transition from Engineering to Data Science
How to Transition from Engineering to Data Science AI for engineers: experience of an engineering graduate Continue reading on Towards Data Science » Dan Pietrow Go to original source
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170 | Formalizing Design with Gabrielle Mérite and Alan Wilson
170 | Formalizing Design with Gabrielle Mérite and Alan Wilson Data design systems and styleguides are currently a huge trend in the data design world. Moritz is joined by Gabrielle Mérite and Alan Wilson and together we exchange experiences in this emerging space, from designing dataviz components as part of Adobe Spectrum, the styleguide for Deloitte’s Insights…
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169 | Data Conversations with Vidya Setlur
169 | Data Conversations with Vidya Setlur We have Vidya Setlur on the show to talk about the role language, and natural language processing (NLP) play in data visualization and analytics. Vidya is the director of research at Tableau and has a background in natural language processing and visualization. She is one of the main drivers behind…
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167 | Visualization and Statistics with Andrew Gelman and Jessica Hullman
167 | Visualization and Statistics with Andrew Gelman and Jessica Hullman In this new episode, we talk about the interplay between statistics and data visualization. We do that with Andrew Gelman, Professor of Statistics and Political Science at Columbia University, and Jessica Hullman, Professor of Computer Science at Northwestern University. Andrew started the popular blog “Statistical Modeling,…
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166 | Catching up with Amanda Makulec
166 | Catching up with Amanda Makulec Hey all, we are back! In this episode, we have Amanda Makulec to catch up on what happened during this whole period of time. Amanda is a public health and data visualization expert and she is the Executive Director of the Data Visualization Society. In the episode, we talk about…
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Should I try to become a Data scientist or AI engineer
Should I try to become a Data scientist or AI engineer Background: I’m a 25M with 2.5 years experience as an analyst. (Soon enrolling in a masters program in CS) There are a few careers possibilities for me, but I’m confused as to whether I should try to become a general data scientist or ai…
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Addressing Missing Data
Addressing Missing Data Understand missing data patterns (MCAR, MNAR, MAR) for better model performance with Missingno Continue reading on Towards Data Science » Gizem Kaya Go to original source