Last month we fine-tuned 25+ #Mistral adapters that rival #GPT4. Since then, we've fine-tuned #Gemma, #Llama, #Zephyr and other LLMs for the same tasks. Join our upcoming webinar to learn which #LLMs performed the best and how to fine-tune your own LLMs! https://
pbase.ai/49OBv0y
MACHINE LEARNING
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Fine-tuning 25+ Mistral Adapters Rivaling GPT-4 Performance
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Snorkel AI CEO Addresses Machine Learning Data-Centric Development
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Snorkel AI CEO Alex Ratner addressed ML's "last mile" problem in October. He gave an overview of state-of-the-art techniques and tools for handling all stages of data-centric development for foundation models. https://
youtube.com/watch?v=g_LyOo
IYRR4
… #AI #DataCentricAI #FoundationModels -
Language Model Advantages and Training Data Optimization Strategies
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It's a very amusing thought for sure! Big advantage to languages that have more training data, in both programming (Python / C), and in spoken language (English) 🙂
I'm cautiously optimistic though. Either by dumping docs into contexts, or via synthetic data means. -
Introduction to Algorithms Third Edition Book Recommendation
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Introduction to #Algorithms (3rd edition): http://
amzn.to/3LsfrwT (~1700 five-star reviews)
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#Mathematics #ComputerScience #Coding #DataScience #MachineLearning #AI #Statistics #ComputationalScience -
Automating Software Engineering: Levels of Autonomy and Abstraction
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# automating software engineering
— Andrej Karpathy (@karpathy) 12 mars 2024
In my mind, automating software engineering will look similar to automating driving. E.g. in self-driving the progression of increasing autonomy and higher abstraction looks something like:
1. first the human performs all driving actions… https://t.co/u2EXfxcV6e# automating software engineering In my mind, automating software engineering will look similar to automating driving. E.g. in self-driving the progression of increasing autonomy and higher abstraction looks something like: 1. first the human performs all driving actions
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Causal AI and Bayesian Networks: Essential Resources and References
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Causal #AI and Bayesian Networks (680-pg PDF eBook): http://
web4.cs.ucl.ac.uk/staff/D.Barber
/textbook/240415.pdf
… See @yudapearl
's BOOK OF WHY: http://
amzn.to/3dRGjGo
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#BigData #IoT #DataScience #Statistics #AI #MachineLearning #LinkedData #Causality #NetworkScience #PredictiveAnalytics #PrescriptiveAnalytics -
Comprehensive Resources on Outlier Detection and Anomaly Analysis Techniques
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[PDF] Extensive Tutorial on #OutlierDetection Techniques: http://
bit.ly/3LzhGxJ Comprehensive textbook on Outlier Analysis: http://
amzn.to/2HTuEv3
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#BigData #DataScience #AI #MachineLearning #Statistics #IoT #IIoT #Edge #EdgeComputing #TimeSeries #AnomalyDetection -
Python Data Science Solutions for Business Challenges
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Dive into #DataScience — Use #Python To Tackle Tough Business Challenges: http://
amzn.to/47wxGfx
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#BigData #Statistics #Analytics #DataAnalytics #AI #MachineLearning #DataLiteracy #DataScientists #Coding #Martech #ABTesting #Forecasting #NLProc #WebScraping #SQL #CDO #CMO -
Modern Python Cookbook Second Edition 822 Pages 133 Recipes
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Modern #Python Cookbook (822 pages, 133 recipes, 2nd Edition): http://
amzn.to/2Xy70bU via @PacktPublishing @PacktAuthors
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#BigData #DataScience #DataScientists #Coding #Statistics #AI #MachineLearning #BeDataBrilliant #100DaysOfCoding #ComputationalScience -
Essential Math Fundamentals for Data Science and Machine Learning
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Essential Math for #DataScience — Take Control of Your Data with Fundamental #LinearAlgebra, #Calculus, #Probability, and #Statistics: http://
amzn.to/47GEBCZ
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#Mathematics #BigData #Analytics #MachineLearning #AI #DeepLearning #DataScientists #Algorithms