🔍 Minimal examples of machine learning tests for implementation, behaviour, and performance.
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Updated
Sep 21, 2022 - Python
🔍 Minimal examples of machine learning tests for implementation, behaviour, and performance.
Measure and visualize machine learning model performance without the usual boilerplate.
A High-level Scorecard Modeling API | 评分卡建模尽在于此
🎓 2020 Undergraduate Graduation Project in Jiangnan University ALL codes including Data-convert, keras-Train, model-Evaluate and Web-App
Valor is a centralized evaluation store which makes it easy to measure, explore, and rank model performance.
Evaluate the performance of computer vision models and prompts for zero-shot models (Grounding DINO, CLIP, BLIP, DINOv2, ImageBind, models hosted on Roboflow)
Titus 2 : Portable Format for Analytics (PFA) implementation for Python 3.4+
skrobot is a Python module for designing, running and tracking Machine Learning experiments / tasks. It is built on top of scikit-learn framework.
Python tools for the AeroCom project
[ICLR 2024] Beyond Accuracy: Evaluating Self-Consistency of Code Large Language Models with IdentityChain
Predict next number in a sequence using a simple ANN. Modularized code with classes for data preparation, neural network architecture, and training.
Luna ML - ML Leaderboard for your team with automatic model evaluation
Explore credit card approval prediction through data analysis and machine learning. Preprocess data, train logistic regression models, and optimize hyperparameters. Learn data preprocessing, feature engineering, model training, and evaluation. Dive into the world of machine learning with Python and popular libraries.
A collection of templates of various machine learning and deep learning algorithms
Fine-tuning GPT-2 models with custom text corpora, utilizing Hugging Face's Transformers library and advanced training techniques for sophisticated text generation applications.
Python library aimed at optimizing the model evaluation process
Quantization Aware Training
A Simple Yet Powerful Machine Learning Python Library
In the project, the aim is to generate new song lyrics based on the artist’s previously released song’s context and style. We have chosen a Kaggle dataset of over 57,000 songs, having over 650 artists. The dataset contains artist name, song name, a link of the song for reference & lyrics of that song. We tend to create an RNN character-level la…
This repository hosts code for a machine learning-based credit card fraud detection project.
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