AWS Machine Learning Blog

JUNE 20, 2024

A score of 1 means that the generated answer conveys the same meaning as the ground truth answer, whereas a score of 0 suggests that the two answers have completely different meanings. The score ranges from 0–1, with higher scores indicating greater semantic similarity between the two answers.

Auto-classification 137

Auto-classification LLM Prompt Engineering Prompt Engineer 137

Mlearning.ai

JULY 22, 2023

the UI for annotation, image ref: [link] The base containers that run when we put the CVAT stack up (not included auto annotation) (Semi) automated annotation The CVAT (semi) automated annotation allow user to use something call nuclio , which is a tool aimed to assist automated data science through serverless deployment.

Auto-complete 52

Auto-complete Computer Vision Automation Metadata 52

ODSC - Open Data Science

AUGUST 24, 2023

Evaluating Prompt Completion: The goal is to establish effective evaluation criteria to gauge LLMs’ performance across tasks and domains. Auto Eval Common Metric Eval Human Eval Custom Model Eval 3. Various prompting techniques, such as Zero/Few Shot, Chain-of-Thought (CoT)/Self-Consistency, ReAct, etc.

Prompt Engineer 52

Prompt Engineer Prompt Engineering Large Language Models Responsible AI 52

PyImageSearch

OCTOBER 2, 2023

in their paper Auto-Encoding Variational Bayes. script sets up the autoencoder model hyperparameters and creates an output directory for storing training progress metadata, model weights, and post-training analysis plots. Auto-Encoding Variational Bayes. VAEs were introduced in 2013 by Diederik et al. The config.py The torch.nn

Computer Vision 105

Computer Vision Deep Learning Neural Network Auto-complete 105

The MLOps Blog

FEBRUARY 27, 2023

Michal, to warm you up for all this question-answering, how would you explain to us managing computer vision projects in one minute? You would address it in a completely different way, depending on what’s the problem. Michal: As I explained at some point to me, I wouldn’t say it’s much more complex.

Computer Vision 52

Computer Vision Auto-classification Auto-complete ML 52

The MLOps Blog

MARCH 12, 2024

Model management Teams typically manage their models, including versioning and metadata. Observability tools: Use platforms that offer comprehensive observability into LLM performance, including functional logs (prompt-completion pairs) and operational metrics (system health, usage statistics). using techniques like RLHF.)

Prompt Engineering 52

Prompt Engineering Prompt Engineer Large Language Models LLM 52

Dlabs.ai

JANUARY 16, 2023

We can well explain this in a cancer detection example. Using new_from_file only loads image metadata. If any of the observations in a bag has a positive label, the whole bag is considered positive. Otherwise, the entire bag is considered negative. The model is trained on bags of observations. A CSV file guides execution.

Neural Network 52

Neural Network ML Auto-classification Convolutional Neural Networks 52

AWS Machine Learning Blog

NOVEMBER 14, 2024

Transparency and explainability : Making sure that AI systems are transparent, explainable, and accountable. However, explaining why that decision was made requires next-level detailed reports from each affected model component of that AI system. It can take up to 20 minutes for the setup to complete.

ML 104

ML Machine Learning Auto-complete Auto-classification 104

AWS Machine Learning Blog

SEPTEMBER 11, 2024

Additionally, this section explains how HyperPod provides a smooth developer experience for admins and scientists. Job auto resume – SageMaker HyperPod provides a job auto resume capability using the Kubeflow Training Operator for PyTorch to provide recovery and continuation of training jobs in the event of interruptions or failures.

Auto-complete 88

Auto-complete ML Machine Learning Automation 88

AWS Machine Learning Blog

AUGUST 6, 2024

The following diagram shows how MusicGen, a single stage auto-regressive Transformer model, can generate high-quality music based on text descriptions or audio prompts. When working with music generation models, it’s important to note that the process can often take more than 60 seconds to complete. Create a Hugging Face model.

Auto-complete 108

Auto-complete Metadata Generative AI Deep Learning 108

AWS Machine Learning Blog

JANUARY 9, 2025

DSX provides unmatched prevention and explainability by using a powerful combination of deep learning-based DSX Brain and generative AI DSX Companion to protect systems from known and unknown malware and ransomware in real-time. This situation hampers proactive threat hunting and exacerbates team burnout.

Deep Learning 115

Deep Learning Neural Network Explainability AI 115