Infographic: How to handle missing data. #Python3 #python #BigData #Analytics #DataScience #AI #MachineLearning #IoT #PyTorch #RStats #TensorFlow #Java #JavaScript #ReactJS #CloudComputing #DataScientist #Programming #Coding #100DaysofCode
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Core Technologies and Tools Powering Data Science Today
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Infographic: The Heart of Data Science #Python3 #python #BigData #Analytics #DataScience #AI #MachineLearning #IoT #PyTorch #RStats #TensorFlow #Java #JavaScript #ReactJS #Tableau #DataScientist #Programming #Coding #100DaysofCode
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Non-AR Models and Output Distribution Evaluation Methods
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Non AR models that expressively model the output distribution do not escape this problem. Issue is more with evaluating with point estimates. This one from Kingma is pretty accurate. https://
x.com/dpkingma/statu
/dpkingma/status/1667239246938402816
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AI and Machine Learning Accelerate Consumer Deal Psychology Research
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How AI And Machine Learning Can Help Accelerate Studies Of Consumer Deal Psychology
#AI #AIio #BigData #ML #NLU #Futureofwork @CRudinschi @AntonioSelas @alexjc @RobotLaunch @karpathy @andyjankowski @bobgourley @CadeMetz http://
ow.ly/Wo1k30svHTA -
Databricks Data AI Summit: 200+ Technical Sessions on Modern Data Stack
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World’s largest #data and #AI conference? @databricks
' #DataAISummit! With a focus on building the modern #DataStack with #Lakehouse, you'll be privy to 200+ technical sessions and keynotes. We're partner sponsors—visit Booth 35! Join us: http://
ow.ly/mPlE50OGkXY -
Alteryx Wins Multiple Awards for Analytics Excellence
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It's nice to be appreciated, and we are certainly feeling it! Alteryx has been lucky enough to win several awards over the last few months – check out our latest blog post to see the roundup. https://
ow.ly/eU6Q50OJw4v #AnalyticsForAll -
How AI is Helping Astronomers Study the Universe
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How AI is helping astronomers study the universe
#AI #AIio #BigData #ML #NLU #Futureofwork @IIoT_World @ipfconline1 @jblefevre60 @JimMarous @insurtechtalk @KirkDBorne @kuriharan @LouisSerge http://
ow.ly/6Ayi30svHUc -
Custom Parallel Data Pipeline for Trillion Token Deduplication
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It was no mean feat to deduplicate data on this scale – existing tools does not scale to a trillion tokens. We built a custom parallel data pre-processing pipeline and are sharing the code open source with the community.
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SlimPajama: 50% Smaller, Twice Faster LLM Training Dataset
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SlimPajama cleans and deduplicates RedPajama-1T, reducing the total token count and file size by 50%. It's half the size and trains twice as fast! It’s the highest quality dataset when training to 600B tokens and when upsampled performs equal or better than RedPajama.
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SlimPajama: High-Quality Dataset Reduces Duplicates Training
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RedPajama-1T is the largest open dataset today but contains a large percentage of duplicates, making a full training run costly and inefficient. Like the Falcon team, we found data quality is just as important as quantity – which led to SlimPajama.