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263 видео
How to Handle Unavailable Data in Open Source Models? #shorts
How Snorkel Flow's labeling functions boost coverage and model performance fast!
The Essential Design Principles Driving AI Engineering
LLM Evaluation for Production Enterprise Applications
Three Ways to Evaluate LLMs
The Future of Data-Centric AI 2021: Full Conference Recording
Why You Should Never Fully Trust a Reward Model
The Benefits of Programmatic Labeling in Building a Spam Classifier
How Cleanlab Uses AI To Correct Errors In Any Dataset
How to Add/Remove/Manage Foundation Models (FMs) and Large Language Models (LLMs) in Snorkel Flow
DEMO: How to Evaluate Enterprise LLMs in Snorkel Flow
How to Upload Images and PDFs into Snorkel Flow
How Snorkel Flow Enables Safe and Responsible AI Development
How to Evaluate LLM Performance for Domain-Specific Use Cases
How to Improve Data and Modeling for Computer Vision Apps
LLM customization made easier with synthetic data sets for specialized domains
What are vision language models (
How to leverage Google Gemini Pro in Snorkel Flow
How vision language models (
RAG Optimization: A Practical Overview for Improving Retrieval Augmented Generation
Topic chunking boosts question-answering accuracy with large language models
How to Handle Unavailable Data in Open Source Models?
Revolutionizing Enterprise AI Alignment with Programmatic Labeling
Integrating Structured and Unstructured Data for Better AI Solutions
How reusable are custom domain rules? (Spoiler: not very!)
Andrew Ng’s Tips for the Data-Centric AI Future
Extracting Insights From Climate Change Research with NLP
How To Select Data for Data-Centric AI
How to Create Data-Cleaning Auto-Pipelines With Python
ML Research Review: SliceLine for Fast Debugging
Data-centric AI for iterating on vast data sets: Andrew Ng's view
Foundation Models Tutorial, and Why Not to Fine Tune Them
How to align LLMs to Enterprise Objectives and Policies
Large Language Models Can Help Make Better Image Classifiers. Here's How.
Alfred: An Open-Source Tool for Building Training Data with Foundation Models and Weak Supervision
How to Fine-Tune LLMs to Perform Specialized Tasks Accurately
What is Active Learning? Machine Learning Expert Shares
We Need Thousands of Research Papers to Flesh Out Data-Centric AI, Andrew Ng
When, Why and How to Fine-Tune LLMs for Enterprise Applications
How New Research Extends Weak Supervision Beyond Classification Problems
LLM Distillation: How Step-by-Step LLM Distillation Yields Incredible Results
How to Optimize RAG Pipelines for Domain- and Enterprise-Specific Tasks
The Iterative LLM Development Loop in Snorkel Flow
The LLM application iteration loop within Snorkel Flow
