#dataScience
Using a DataClassroom simulation you can decide on your experimental variables, think more deeply about what to measure, and try out visualizations - all before you go to the lab!

https://about.dataclassroom.com/blog/plan-an-experiment-with-simulation

#DataScience #TeachingStats #DataLiteracy
November 12, 2025 at 10:34 AM
LLM-based tools are very good for summarizing (use case: internal datasets), exploring or ideating hypotheses (to a certain degree), and performing basic intern-level data cleaning and data exploration. When one tries to overexpect, things fall apart.

#GenAI #DataScience
November 12, 2025 at 10:01 AM
Tests for the significance of marginal effects in the teller

https://thierrymoudiki.github.io/blog/2019/11/08/explainableml/the-teller-2

#Techtonique #DataScience #Python #rstats #MachineLearning
November 12, 2025 at 8:33 AM
Calling =TECHTO_MLCLASSIFICATION for Machine Learning supervised CLASSIFICATION in Excel is just a matter of copying and pasting

https://thierrymoudiki.github.io/blog/2025/07/07/r/python/techto-ml-classif

#Techtonique #DataScience #Python #rstats #MachineLearning
November 12, 2025 at 8:33 AM
The Three Ages of Data Science: When to Use Traditional Machine Learning, Deep Learning, or an LLM (Explained with One Example)

A practical use case to describe how the data scientist job changed across three generations of machine le…

Telegram AI Digest
#datascience #deeplearning #machinelearning
The Three Ages of Data Science: When to Use Traditional Machine Learning, Deep Learning, or an LLM (Explained with One Example)
A practical use case to describe how the data scientist job changed across three generations of machine learning
towardsdatascience.com
November 12, 2025 at 8:12 AM
Три эпохи науки о данных: когда использовать традиционное машинное обучение, глубокое обучение или LLM (объяснено на одном примере)

Telegram ИИ Дайджест
#datascience #deeplearning #machinelearning
The Three Ages of Data Science: When to Use Traditional Machine Learning, Deep Learning, or an LLM (Explained with One Example)
towardsdatascience.com
November 12, 2025 at 8:00 AM
Nested Learning lets models adapt without forgetting, saving retraining time, but adds complexity and risk of bias propagation. #AI #MachineLearning #ContinualLearning #DataScience #DigitalTransformation
research.google/blog/introdu...
Introducing Nested Learning: A new ML paradigm for continual learning
We strive to create an environment conducive to many different types of research across many different time scales and levels of risk.
research.google
November 12, 2025 at 7:35 AM
#ecology #sustainability #publichealth #SDGs #healthinformatics #ecotologists #CKD #gerontology #datascience #health

Nephrologists have no idea
which priority nephrotoxic pollutant mixtures
need to be documented
for each
- subtype of disease
- age group,
- occupation,
- and geographic region.
November 12, 2025 at 2:54 AM
📢 Join the #dkNET Webinar!
Data-driven Biology with #CFDE CONNECT Community of Resources
🗓️ Fri, Nov 21, 2025 | 🕚 11 am–12 pm PT
Jake Y. Chen, Ph.D., UAB Heersink School of Medicine
Learn how CFDE CONNECT advances data-driven research!
🔗 dknet.org/about/blog/2...

#DataScience
November 11, 2025 at 11:36 PM
November 11, 2025 at 11:32 PM
AI Masterclass leanpub.com/set/leanpub/... by Henrik Kniberg, Obie Fernandez, and Andriy Burkov is the featured Track of online courses on the Leanpub homepage! leanpub.com #DigitalTransformation #Gpt #Ai #SoftwareArchitecture #RubyOnRails #Textbooks #DataScience
November 11, 2025 at 9:45 PM
While editing the new edition of my book, I kept coming back to this: The real value isn’t in the model’s accuracy.
It’s in the clarity of its reasoning, and the trustworthiness of its assumptions.

#DataScience #MachineLearning #AI #RStats
November 11, 2025 at 8:56 PM
Forecasting Professional leanpub.com/b/forecastin... by Valery Manokhin is the featured bundle of ebooks 📚 on the Leanpub homepage! leanpub.com #ComputerScience #MachineLearning #Mathematics #Python #DataScience #DeepLearning #Education

Find it on Leanpub!
November 11, 2025 at 8:45 PM
(News from) Probabilistic Forecasting of univariate and multivariate Time Series using Quasi-Randomized Neural Networks (Ridge2) and Conformal Prediction

https://thierrymoudiki.github.io/blog/2025/03/09/r/ridge2-conformal

#Techtonique #DataScience #Python #rstats #MachineLearning
November 11, 2025 at 8:38 PM
Tuning and interpreting LSBoost

https://thierrymoudiki.github.io/blog/2021/11/15/python/quasirandomizednn/mlsauce/tuning-explaining-lsboost

#Techtonique #DataScience #Python #rstats #MachineLearning
November 11, 2025 at 8:20 PM
Production Ready Data Science: From Prototyping to Production with Python leanpub.com/production-r... by Khuyen Tran is the featured book on the Leanpub homepage! leanpub.com #DataScience #Python #SoftwareEngineering #VersionControl #Git

Find it on Leanpub!
November 11, 2025 at 8:15 PM
🚀 New in Nelson: support for Name=Value syntax!
Write cleaner, more modern code and compatible.
#STEM #OpenSource #HPC #DataScience #DataAnalysis #Programming #ScientificComputing #Coding #OSS #GNUOctave #Scilab #Matlab #NelsonLang
November 11, 2025 at 7:43 PM