Towards Data Science
May 29
Explaining Lineage in DAX
One of the most important concepts in DAX is lineage. It’s about the information on where something comes from.
Automatically Assign a Category to Uncategorized Rows in Power Query and DAX
Having categorized data is everything in reporting. Uncategorized data cannot be grouped and aggregated.
Related stories
Towards Data Science
Aug 7
Loop Engineering for Listing Questions: When the Answer Is Every Passage, Not the Top One
Enterprise Document Intelligence [Vol. 1 #12] - The category of question most RAG pipelines silently fail on, and the pipeline shape that handles them The post Loop Engineering for Listing Questions: When the Answer Is Every Passage, Not the Top One appeared first on Towards Data Science .
Towards Data Science
Jun 21
What Are the Possibilities to Build Date Tables in Self-Service Environments?
For years, I created date tables with DAX code whenever I didn’t have a way to create them upstream of the data flow. Now I've realised there's another way to do it.
Towards Data Science
Jun 20
Materialized Lake Views in Microsoft Fabric: When Your Medallion Fits in a SELECT Statement
Five surfaces collapsed into one declarative layer. Here's the full story of Materialized Lake Views in Microsoft Fabric - from syntax to the new GA capabilities The post Materialized Lake Views in Microsoft Fabric: When Your Medallion Fits in a SELECT Statement appeared first on Towards Data Science .
arXiv AI
Jul 8
Learnable Weighting of Intra-Attribute Distances for Categorical Data Clustering with Nominal and Ordinal Attributes
arXiv:2607. 05464v1 Announce Type: cross Abstract: The success of categorical data clustering generally much relies on the distance metric that measures the dissimilarity degree between two objects.
Towards Data Science
Jul 17
A Production RAG Pipeline in Action: Every Answer Typed and Cited
Enterprise Document Intelligence [Vol. 1 #9B] - One call wires the four upgraded bricks together, run on a paper, a NIST standard, and a report with a broken TOC The post A Production RAG Pipeline in Action: Every Answer Typed and Cited appeared first on Towards Data Science .
Towards Data Science
Aug 5
Introduction to Semi-Supervised Learning
A primer about Semi-Supervised Learning, the approaches taken with different algorithms and the limitations of using unlabelled data. The post Introduction to Semi-Supervised Learning appeared first on Towards Data Science .
arXiv AI
Jun 30
Categorizing Mathematical Concepts with LLM Voting Ensembles in Mathswitch
arXiv:2606. 28815v1 Announce Type: cross Abstract: Mathswitch is an open-source project that imports mathematical concept records from sources such as Wikidata, Wikipedia, MathWorld, Encyclopedia of Mathematics, nLab, ProofWiki, and Agda-Unimath, and links records that refer to the same concept.
arXiv Machine Learning
Aug 5
To Describe or Construct Statistical Learning Models Using the Category-theoretical Language
arXiv:2608. 03706v1 Announce Type: new Abstract: Statistical learning is a fascinating field that has long been the mainstream of machine learning/artificial intelligence.
Hugging Face Trending Papers
Aug 4
To Describe or Construct Statistical Learning Models Using the Category-theoretical Language
Statistical learning is a fascinating field that has long been the mainstream of machine learning/artificial intelligence. A large number of results have been produced which can be widely applied to real-world problems.
Towards Data Science
Jul 5
Assemble Each RAG Generation Prompt from a Base Prompt Plus the Rules Each Question Needs
Enterprise Document Intelligence [Vol. 1 #8B] - A fixed BASE, the rules each question needs, one registry: the dispatcher that turns a parsed question into a typed LLM call The post Assemble Each RAG Generation Prompt from a Base Prompt Plus the Rules Each Question Needs appeared first on Towards Data Science .
Towards Data Science
Jun 26
How to Ace Data and ML Behavioural Interviews
How to smash through data / ML behavioural interviews The post How to Ace Data and ML Behavioural Interviews appeared first on Towards Data Science .