Popular GitHub Repositories for Roc Auc Curve

Robyn is an experimental, AI/ML-powered and open sourced Marketing Mix Modeling (MMM) package from Meta Marketing Science. Our mission is to democratise modeling knowledge, inspire the industry through innovation, reduce human bias in the modeling process & build a strong open source marketing science community.

Data Science Notebook on a Classification Task, using sklearn and Tensorflow.

Code for the ICPR 2020 paper: "CURL: Neural Curve Layers for Image Enhancement"

Offical Code of MICCAI'24 early accepted paper "LGRNet: Local-Global Reciprocal Network for Uterine Fibroid Segmentation in Ultrasound Videos"

Autonomous driving trajectory planning solution for U-Turn scenario

Official pytorch version for Self-Reference Deep Adaptive Curve Estimation for Low-Light Image Enhancement

??? This one stop project is a complete COVID-19 detection package comprising of 3 tasks: ? Task 1 --> COVID-19 Classification ? Task 2 --> COVID-19 Infection Segmentation ? Task 3 --> Lung Segmentation

Support vector machines (SVMs) and related kernel-based learning algorithms are a well-known class of machine learning algorithms, for non-parametric classification and regression. liquidSVM is an implementation of SVMs whose key features are: fully integrated hyper-parameter selection, extreme speed on both small and large data sets, full flexibility for experts, and inclusion of a variety of different learning scenarios: multi-class classification, ROC, and Neyman-Pearson learning, and least-squares, quantile, and expectile regression.

PKBoost: Adaptive gradient boosting with biological-inspired metabolism. Autonomous concept drift adaptation. 80% PR-AUC improvement over XGBoost on imbalanced datasets.

Polish bird species recognition - Bird song analysis and classification with MFCC and CNNs. Trained on EfficientNets with final score 0.88 AUC. Women in Machine Learning & Data Science project.

Parametric differentiable curves with PyTorch for continuous embeddings, shape-restricted models, or KANs

Machine learning toolkits with Python

Point Projection On Parametric Curves / Trajectory Maps for Autonomous Driving

End-to-end sentiment analysis of tweets using BERT. Includes preprocessing, training, and evaluation with classification reports, confusion matrices, ROC curves, and word clouds. Demonstrates fine-tuning of transformer models for text classification with modular, reproducible code.

Unleash the full potential of exascale LLMs on consumer-class GPUs, proven by extensive benchmarks, with no long-term adjustments and minimal learning curve.

Using R and machine learning to build a classifier that can detect credit card fraudulent transactions.

A PyTorch implementation of a Deep Convolutional GAN (DCGAN) trained on MNIST. Includes training scripts, generator & discriminator models, random sample generation, latent space interpolation, and loss curve visualization to create realistic handwritten digit images.

stratigraphic machine-learning - active work moved to Predictatops

Landscape of ML/DL performance evaluation metrics

Genetic Algorithm, Curve Fitting, Reinforcement Learning, Iteration Value, Iteration Policy, FrozenLake-v1 Environment, Q-Learning, Hidden Markov Models, ML, Linear Regression, Multiple Regression, Classification, Decision Tree, K-Nearest Neighbors, Logistic Regression, Optimization, Random Forest, Gradient Boosting, XGBoost Classifier