#CS285 Deep #ReinforcementLearning, University of California! #BigData #Analytics #DataScience #AI #MachineLearning #IoT #IIoT #Python #RStats #TensorFlow #JavaScript #ReactJS #CloudComputing #Serverless #Linux #Programming #Coding #100DaysofCode https://
geni.us/CS285-DL-Course
MACHINE LEARNING
-
CS285 Deep Reinforcement Learning Course UC Berkeley
By
–
-
Top Statistics Books for Data Science and Machine Learning
By
–
Top #Statistics #Books to Read! #BigData #Analytics #DataScience #AI #MachineLearning #IoT #IIoT #Python #RStats #TensorFlow #Java #JavaScript #ReactJS #GoLang #CloudComputing #Serverless #DataScientist #Linux #Programming #Coding #100DaysofCode https://
geni.us/Stats-Recomm -
Natural Language Processing Podcast Episode Introduction
By
–
Introducing Podcast Episode for Natural Language Processing! #BigData #Analytics #DataScience #AI #MachineLearning #IoT #IIoT #Python #RStats #TensorFlow #JavaScript #ReactJS #Serverless #DataScientist #Linux #Programming #Coding #100DaysofCode https://
geni.us/Intro-NLP-Epis
odes
… -
Fundamental Statistics Concepts for Data Scientists
By
–
Fundamental #Statistics Concepts for #DataScientists! #BigData #Analytics #DataScience #AI #MachineLearning #IoT #IIoT #Python #RStats #TensorFlow #JavaScript #ReactJS #CloudComputing #Serverless #DataScientist #Linux #Programming #Coding #100DaysofCode https://
geni.us/Stats-Con-DSci -
Next Word Prediction and Loss Functions for Model Understanding
By
–
This is a brilliant explanation of why next word prediction is a good loss function to achieve understanding. In addition to predicting the next bit, one can also use masking losses and diffusion to achieve understanding. The general intuition is to minimise the difference… https://t.co/tUDUQWP4NJ
— Nando de Freitas (@NandoDF) 25 mai 2025This is a brilliant explanation of why next word prediction is a good loss function to achieve understanding. In addition to predicting the next bit, one can also use masking losses and diffusion to achieve understanding. The general intuition is to minimise the difference
-
Databricks Releases Compute Tables, AI Genie Enhancements
By
–
Databricks’ Holly Smith and Nick Karpov show some of our newest product releases and updates in action, including:
— Databricks (@databricks) 25 mai 2025
– Compute system tables in GA
– New AI/BI Genie enhancements
– Run code in Databricks Assistant on serverless compute
Hear their take on these updates and more –… pic.twitter.com/vObPZD6WDHDatabricks’ Holly Smith and Nick Karpov show some of our newest product releases and updates in action, including:
– Compute system tables in GA
– New AI/BI Genie enhancements
– Run code in Databricks Assistant on serverless compute Hear their take on these updates and more – -
Top 10 Data Science Myths Busted: Digital Transformation Insights
By
–
New on the Blog: Top 10 Data Science Myths Busted Stay ahead in the ever-evolving world of Digital Transformation. This article explores key insights into emerging technologies and their impact on today's business landscape. Discover how to leverage innovation to drive
-
Blood biomarker AI predicts Alzheimer’s in cognitively unimpaired middle-aged adults
By
–
Predicting Alzheimer's in people who are cognitively unimpaired in middle-age via blood tests p-tau217 did well (best single biomarker), its ratio with Aβ42 had highest performance for detecting PET + amyloid new publication today https://
thelancet.com/journals/ebiom
/article/PIIS2352-3964(25)00185-9/fulltext
… -
Databricks Data AI Summit 2026: Register for World’s Largest Conference
By
–
Why attend #DataAISummit? Networking, technical sessions on data intelligence, engineering, governance, trainings and certifications, parties, and more! Don’t miss out on the world’s largest data, analytics, and AI conference — register now: https://
databricks.com/dataaisummit/o
nsite-experience?utm_source=twitter&utm_medium=organic-social&utm_scid=701vp00000d7qrxia3
… -
GRIT: Teaching MLLMs Grounded Visual Reasoning with Images
By
–
10. Teaching MLLMs to Think with Images GRIT is a new method that enables MLLMs to perform grounded visual reasoning by interleaving natural language with bounding box references.