Edward ‘Big Balls’ Coristine I...
झारखंड में आधार कार्ड घोटाला!
झारखंड में आधार कार्ड घोटाला! | Jharkhand Aadhaar Scam | Sahibganj Aadhaar Fraud| Pakur Aadhaar Irregularities| Fake Aadhaar Cards | Follow us for more local news and updates: 👉 YouTube: 👉 Facebook: 👉 Instagram: 🌐 Website: #jharkhand #aadhaar #aadhaarscam #sahibganj #pakur #csc #commonsservicecenter #identityfraud #governance #illegalactivities #datamanipulation #indianews #securityconcern #bangladeshiinfiltration #investigation…
Belgian Police exposed using botnets to manipulate EU data law impact assessment
https://old.reddit.com/r/europe/comments/1p9kxhm/belgian_federal_police_forgot_to_turn_their_vpn/
#HackerNews #BelgianPolice #Botnets #EULaw #DataManipulation #Cybersecurity
There is a gap in #lowcode tooling for geospatial #datamanipulation, with most existing solutions either proprietary, outdated, or not aligned with the needs of those users wishing for visual tools. #Geoflow, an emerging #opensource project with a visual workflow builder, could evolve into a suitable alternative.
If you’re interested in baseball in particular, or in any other sport where some data sources are available for which a variable needs to be followed over time over the central 50% quartile, this post covers both data reading, transformation, and plotting.
#DataManipulation #DataVisualization #CSV #Python #pandas #matplotlib https://fosstodon.org/@drdrang/115296285675549307
☃️ A post I was supposed to write after the 2023 season https://leancrew.com/all-this/2025/09/baseball-durations-after-the-pitch-clock/
: #data #datamanipulation #datamisrepresentation #democrats #donaldthehoaxtrump #donaldtramp #eightysix47 #presidenttramp #trumpstein #trumpsteincoverup #uspol #uspolitics :
DATA MISREPRESENTATION
Mastodon Post
Get in line. Many of us have already warned of Donald Tramp manipulating and misrepresenting data.
Supametas.AI: Unstructured data ETL platform
Supametas.AI is an unstructured data ETL platform designed to simplify the process of converting various data formats into structured data suitable for LLM RAG (Retrieval-Augmented Generation) applications. It caters to enterprises looking to efficiently collect, construct, and preprocess industry-specific datasets for integration into LLM knowledge bases. Key Features: Versatile Data Collection: Supports data ingestion from multiple sources, including APIs, web pages, local files (docx, pdf, txt, md, json), images (jpg, png), audio (mp3), and video (mov, mp4, mpv). Standardized Output: Extracts data into standard JSON and Markdown formats, ensuring compatibility with various LLM frameworks. LLM RAG Integration: Seamlessly integrates with LLM RAG knowledge bases, including OpenAI Storage and Dify Datasets, with API support for custom integrations. User-Friendly Interface: Offers a zero-threshold, out-of-the-box experience, enabling quick creation of industry datasets. Data Privacy: Provides options for both SaaS and private Docker deployment to address enterprise data privacy needs. Use Cases: Knowledge Base Creation: Rapidly build and maintain LLM knowledge bases with structured data extracted from diverse sources. Data Preprocessing: Streamline data preprocessing pipelines for LLM applications, reducing manual effort and improving data quality. Digital Avatar Data Processing: Process digital human avatar data for use in AI applications. Content Transformation: Transform raw data into desired content formats, boosting productivity and efficiency. Podcast/Video Data Integration: Convert podcast audio and video data into LLM knowledge bases.