If you eg. use a mathematical model that divides by zero, you've got a singularity. But since mathematics does not allow you to divide by zero, you know that your model is wrong.
MACHINE LEARNING
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Fine-tuning LLMs Workshop at MLOpsWorld SF
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Excited to join @MLOpsWorld SF to lead a workshop on Fine-tuning Your Own #LLMs that Rival #GPT4. Join us to learn the benefits, use cases, and techniques for fine-tuning LLMs and get hands-on with popular open-source frameworks #Ludwig and #LoRAX! https://
pbase.ai/3IANSRU -
Claude 3 Opus: Demonstrating ASCII art logo rendering with common but retryable errors
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Demo: Claude 3 Opus renders ASCII art logos LLMs are generally awful at this. Claude 3 is the best yet; errors are common, but with retries you can get legible text. Note how similar the errors are to diffusion models — e.g. bad spelling/glyphs but consistent drop shadows
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Advanced Classification Challenges in Machine Learning with Snorkel
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Curious about how to tackle advanced classification challenges in machine learning? Snorkel's Staff Product Designer Angela Fox and Director of Product/Founding Engineer Vincent Chen dive deep into the subject. Watch the video here: https://
youtube.com/watch?v=PHMye3
EHyLk
… #machinelearning -
Abacus AI Optimization Solvers for Supply Chain and Resource Management
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State-of-the-art #Optimization Solvers from @abacusai can generate optimal solutions for biz problems fast! See: https://
abacus.ai/discrete_optim
ization
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=> Optimize #SupplyChain, Scheduling, & Resources!
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#ERP #SCM #Logistics #Analytics #PrescriptiveAnalytics #AI #MachineLearning #DataScience -
High Cardinality Categorical Data Handling in Query Analysis
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Benchmarking Query Analysis in High Cardinality Situations When returning information in a structured format the fields can be a myriad of types: string, boolean, integers. One of the hardest types to correctly handle is high-cardinality categorical values (or enums). In
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Machine Learning with PyTorch and Scikit-Learn Book 35% Off
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35% OFF regular price
Massive 774-page book by @rasbt => #MachineLearning with #PyTorch and Scikit-Learn: Develop #ML and #DeepLearning models with #Python” at http://
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Artificial Intelligence Modern Approach Fourth Edition Book Recommendation
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Artificial Intelligence — A Modern Approach
[4th Ed.] http://
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#AI #BigData #DataScience #MachineLearning #ML #TransferLearning #DeepLearning #Algorithms #Mathematics #NeuralNetworks #NLProc #ComputerVision #ReinforcementLearning #ArtificialIntelligence -
Pretraining Vision and LLMs in Python on AWS
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Pretrain Vision and #LLMs (Large Language Models) in #Python — Techniques for building & deploying foundation models on #AWS: http://
amzn.to/3pT9seD via @PacktPublishing ————
#AI #MachineLearning #DeepLearning #MLOps #BigData #DataScience #NLProc #ComputerVision #DataScientists -
Master NLP: From Foundations to Large Language Models
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Mastering #NLProc from Foundations to #LLMs — Apply Advanced NLP Techniques to Solve Real Business Problems: https://
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@PacktPublishing release May 9. Pre-order now for price guarantee.)
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#DataScience #GenerativeAI #AI #MachineLearning #DeepLearning #GenAI