📚 A curated list of papers & technical articles on AI Quality & Safety
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Updated
Apr 14, 2025
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📚 A curated list of papers & technical articles on AI Quality & Safety
machine-learning natural-language-processing awesome ai computer-vision ml artificial-intelligence awesome-list ai-safety model-validation robustness mlops ai-alignment model-testing ml-safety ethical-ai ml-testing llm llmops ai-quality
Eval framework. Define correct, test against it, get results.
golang benchmark machine-learning evaluation quality-assurance automated-testing benchmark-suite model-evaluation evaluation-framework testing-framework model-testing ai-evaluation ai-testing ai-quality llm-evaluation inference-testing ai-benchmarking eval-framework eval-driven-development mist-stack
Abstract Constraint Transformation
abstract-interpretation model-verification model-testing neural-network-verification concept-based-explanations ai-testing ai-verification abstract-constraint-transformation model-fuzzing neural-network-testing static-analysis-of-ai-models
Implements an entire machine learning pipeline to train and evaluate a Random Forest Classifier on labeled gait data for walking. Data generated during the experiment has led to helpful insights in to the problem domain.
python machine-learning random-forest scikit-learn data-visualization feature-selection feature-extraction classification supervised-machine-learning model-training step-detection gait-analysis rfe rfecv data-pre-processing step-counting model-testing
This project promulgates an automated end-to-end ML pipeline that trains a biLSTM network for sentiment analysis, experiment tracking, benchmarking by model testing and evaluation, model transitioning to production followed by deployment into cloud instance via CI/CD
nlp docker aws airflow deep-neural-networks tensorflow snowflake ci-cd orchestration ec2-instance datawarehouse bilstm mlops mlflow github-actions sagemaker-deployment model-testing automated-pipeline
Assignment-04-Simple-Linear-Regression-2. Q2) Salary_hike -> Build a prediction model for Salary_hike Build a simple linear regression model by performing EDA and do necessary transformations and select the best model using R or Python. EDA and Data Visualization. Correlation Analysis. Model Building. Model Testing. Model Predictions.
python numpy smf eda pandas data-visualization seaborn p-value model-predictions feature-engineering ols-regression statsmodels model-building simple-linear-regression correlation-analysis t-score model-testing distplot regression-plot r-square-values
Grok 场景路由交付合约 · 模型安全研究
📝🔍🖼️ A deep learning application for retrieving images by searching with text.
python nlp natural-language-processing computer-vision deep-learning word2vec pytorch pytest image-search convolutional-neural-networks image-retrieval multimodal-learning multimodal-deep-learning mlops github-actions machine-learning-testing model-testing streamlit koushikvikram koushik-vikram
SDK for Inquire model test database API, by Sevan
Simple DB Fixtures for Sails.js v1 (fake data for testing).
A deterministic simulation and model testing toolkit for MoonBit with virtual time, seeded randomness, trace/replay, metrics, scenarios, and reusable model tests.
A python package, command-line tool, and Shiny application to compare short tandem repeat (STR) profiles.
LLM drift detector — know within 5 min when GPT-4o, Claude, or Gemini silently changes behaviour. Open source, self-hostable.
saas gemini openai regression-testing gpt claude mlops drift-detection production-ml model-testing ai-monitoring llm llmops prompt-testing llm-monitoring llm-observability behavioral-testing
Image Classifiers are used in the field of computer vision to identify the content of an image and it is used across a broad variety of industries, from advanced technologies like autonomous vehicles and augmented reality, to eCommerce platforms, and even in diagnostic medicine.
python aws json aws-lambda aws-s3 image-classification aws-ec2 endpoint model-evaluation aws-step-functions sagemaker sagemaker-deployment model-testing aws-statemachine sagemaker-studio model-inference
ai cnn artificial-intelligence artificial-neural-networks augmentation polynomial-arithmetic model-training cnn-classification fashion-mnist model-train fashion-mnist-dataset model-testing model-test
Real-Time Fatigue Monitoring with Dual CNN Models for Face & Eye Status. This is a real-time safety system designed to monitor driver alertness using Tensorflow. Built from scratch using Convolutional Neural Networks (CNNs), the system tracks eye and face status independently and triggers alerts when signs of drowsiness exceed a defined threshold.
machine-learning deep-learning image-processing neural-networks convolutional-neural-networks binary-classification model-evaluation model-testing
Assignment-04-Simple-Linear-Regression-1. Q1) Delivery_time -> Predict delivery time using sorting time. Build a simple linear regression model by performing EDA and do necessary transformations and select the best model using R or Python. EDA and Data Visualization, Feature Engineering, Correlation Analysis, Model Building, Model Testing and Mo…
python numpy smf eda pandas data-visualization seaborn p-value model-predictions feature-engineering ols-regression statsmodels model-building simple-linear-regression correlation-analysis rsquare-values t-score model-testing distplot regression-plot
Behavioral regression testing for AI model changes in Spring AI applications.
Successfully developed a machine learning model which can accurately predict up to 100% accuracy whether a credit card application of a given applicant would be approved or not, based on several demographic features such as applicant age, total income, marital status, total years of work experience, etc.
machine-learning exploratory-data-analysis cross-validation data-visualization model-selection hyperparameter-optimization feature-engineering binary-classification model-deployment model-retraining model-testing cicd-deployment model-training-and-evaluation data-exploration-and-preprocessing
Supervised-ML-Decision-Tree-C5.0-Entropy-Iris-Flower-Using Entropy Criteria - Classification Model. Import Libraries and data set, EDA, Apply Label Encoding, Model Building - Building/Training Decision Tree Classifier (C5.0) using Entropy Criteria. Validation and Testing Decision Tree Classifier (C5.0) Model
python entropy numpy sklearn matplotlib decision-trees decision-tree-classifier classification-report model-validation model-building sklearn-dataset model-testing train-test-split sklearn-tree label-encoder
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