2 repositorios
Awesome GitHub RepositoriesBinary Classification Training
Training workflows for models that predict one of two possible outcomes from input features.
Distinct from Model Training: Distinct from Model Training: specifically targets binary classification with sparse and dense features, not general training.
Explore 2 awesome GitHub repositories matching artificial intelligence & ml · Binary Classification Training. Refine with filters or upvote what's useful.
Awesome Binary Classification Training GitHub Repositories
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- jack-cherish/machine-learning
Jack-Cherish/Machine-Learning
10,333Ver en GitHubThis project is a collection of supervised and unsupervised machine learning algorithms implemented from scratch using Python. It serves as an educational resource for studying model training, parameter optimization, and the implementation of core predictive models. The library provides a variety of supervised learning tools, including linear and logistic regression, decision trees, and support vector machines. It also features unsupervised learning capabilities for discovering patterns in unlabeled datasets through clustering algorithms. Broad capability areas include ensemble learning thro
Implements binary classification using a logistic function to map input features to a binary outcome probability.
Pythonadaboostadaboost-algorithmdecision-tree - shenweichen/deepctr-torch
shenweichen/DeepCTR-Torch
3,376Ver en GitHubDeepCTR-Torch is a deep learning library for building click-through rate prediction models. It provides a modular framework for assembling custom prediction architectures from pre-built core, interaction, and sequence layers, enabling the construction of deep neural networks that estimate click probability from user behavior data. The library specializes in feature interaction modeling, offering components for learning low-order, high-order, and adaptive-order feature crosses. It supports multi-task learning for predicting multiple objectives simultaneously, such as click and conversion rates
Train a deep learning model on sparse and dense features to predict a binary outcome like ad click-through rate.
Pythonctr-modelsdeep-learningdeepctr
