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Many #datascience techniques depend on the assumption that #data are normally distributed. How can you tell whether that's the case, and what do you do if it isn't? This tutorial explains. #statistics https://t.co/vYep7FnLwd
This study concludes that while 97.2% of companies invest in big data solutions, most of these companies only use 37%-40% of their #data in their #analytics. https://t.co/CCCCrqxKMZ
What do you do when LLMs get too large to run on available hardware? One option is to use quantization. This blog post introduces the concept of quantization and how to employ it. #AI#MachineLearning#DataScience https://t.co/VRdK5hKKB4
A new era of business intelligence is here! As companies race to implement #AI, @tableau is introducing Tableau Next - an AI-powered platform within @salesforce. At its core is Agentforce, Salesforce’s AI layer, bringing agentic AI directly into #analytics https://t.co/EQ66rSv68z
Bayesian Structural Time Series (BSTS) is a great way to build a probabilistic component into your time series forecasting models. Here's a guide to BSTS with sample code in R. #statistics#DataScience#data https://t.co/OerI38GPYn
The tips shared in this article can help you avoid "death by ROI" in your organization's data-oriented processes. #data#analytics https://t.co/NLOg4wFCse
When training an LLM, the transparency of the dataset it's built on is paramount. This article explains a tool that researchers have created to ensure the transparency of a training set. @MIT#AI#DataScience#MachineLearning https://t.co/wakTZTNzSP
Streamgraphs are a type of stacked area chart that shows components of a total, typically over time. This article introduces streamgraphs and also provides graph galleries in #R, #Python, #React, and D3. ##data#analytics#DataViz https://t.co/C6f0lwgQNC
This article explains the purposes and usages of the Walrus operator within #Python, one of the most underutilized of all Python's capabilities. #data#analytics https://t.co/oSQJXX9uJm
Are you familiar with waffle charts? An interesting alternative to pie charts and segmented bar charts, waffle charts show proportional #data or percentage completion towards a goal. #analytics#DataViz https://t.co/9aZZPiCggh
If you're using @Snowflake and you want to perform a "fuzzy match" on records that don't exactly match, you should check out the JAROWINKLER_SIMILARITY function. #SQL#dbms#data#Snowflake https://t.co/0tBblXZMQf
Spreadsheets that have been formatted to look visually appealing to humans can present challenges when you have to use the #data programmatically. This blog post shares some ideas on how to best accommodate formatted datasets in #R. #analytics https://t.co/d0Hkc4HZXs
Missing data is a problem that every data scientist and data analyst has to deal with at some point. This video explains some of the things to avoid when dealing with missing #data. #analytics https://t.co/DDehrmlxzK
This article explores the meteoric rise of the market for #data and #analytics tools over the past several years. #DataScience@VentureBeat https://t.co/4dwLd2IkEr
Survey #data can be immensely valuable to organizations that collect it, but its usage also has some risks. This article presents some of the pros and cons of survey data. @Genroe#analytics https://t.co/EvqiDNdxNx
If you're learning or upskilling in #R, the dplyr package is one of the most important topics to cover. This blog post shows visually how some of the key methods within dplyr work. #data#analytics https://t.co/mfREptcNJA