article thumbnail

A quantum-optimized approach for breast cancer detection using SqueezeNet-SVM

Flipboard

The proposed Q-BGWO-SQSVM was evaluated using diverse databases: MIAS, INbreast, DDSM, and CBIS-DDSM, analyzing its performance regarding accuracy, sensitivity, specificity, precision, F1 score, and MCC.

article thumbnail

How IDIADA optimized its intelligent chatbot with Amazon Bedrock

AWS Machine Learning Blog

To determine the best parameter values, we conducted a grid search with 10-fold cross-validation, using the F1 multi-class score as the evaluation metric. Document_Translation Please translate the file Product_Manual.xlsx into English Document_Translation Could you convert the document Data_Privacy_Policy.doc into English, please?

professionals

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

Visier’s data science team boosts their model output 10 times by migrating to Amazon SageMaker

AWS Machine Learning Blog

Tedious data engineering tasks like pulling data into the environment and database infrastructure costs were eliminated by securely storing their vast amount of customer-related datasets within Amazon Simple Storage Service (Amazon S3) and using Amazon Athena to directly query the data using SQL.

article thumbnail

The Evolution of Tabular Data: From Analysis to AI

Towards AI

It encompasses everything from CSV files and spreadsheets to relational databases. This is unsurprising as winning solutions are often based on simple models but involve extensive feature selection, cross-validation, data augmentation, and ensemble techniques.

article thumbnail

Best Egg achieved three times faster ML model training with Amazon SageMaker Automatic Model Tuning

AWS Machine Learning Blog

To reduce variance, Best Egg uses k-fold cross validation as part of their custom container to evaluate the trained model. He is passionate about databases, machine learning, and designing innovative solutions. Best Egg runs SageMaker training jobs with automated hyperparameter tuning powered by Bayesian optimization.

ML 101
article thumbnail

Mastering ML Model Performance: Best Practices for Optimal Results

Iguazio

In some cases, cross-validation techniques like k-fold cross-validation or stratified sampling may be used to get more reliable estimates of performance. Consider performing this tuning within a cross-validation framework to avoid overfitting to a specific test set.

ML 52
article thumbnail

Artificial Intelligence Using Python: A Comprehensive Guide

Pickl AI

Public Datasets: Utilising publicly available datasets from repositories like Kaggle or government databases. Python supports diverse model validation and evaluation techniques, which are crucial for optimising model accuracy and generalisation. Web Scraping : Extracting data from websites and online sources.