该代码的目的是训练机器学习模型（特别是梯度增强分类器），以根据数据实例的特征将其分类为不同的类。
The purpose of this code is to train a machine learning model (specifically a gradient boosting classifier) to classify data instances into different classes based on their features. (2024-03-25, Jupyter Notebook, 0KB, 下载0次)
该项目涉及进行全面的探索性数据分析（EDA），并使用Scikit Learn TensorFlow采用了有效的模型，如人工神经网络（ANN）、梯度提升分类器等。
The project involved conducting a comprehensive Exploratory Data Analysis (EDA) and employed efficient models such as Artificial Neural Networks (ANN), Gradient Boosting Classifiers, and others, using Scikit-Learn TensorFlow. (2024-03-09, Jupyter Notebook, 0KB, 下载0次)
在Python中使用关键字搜索和语义搜索实现产品搜索自动完成。对于关键字搜索，使用Fuzz库，对于语义搜索，使用带Faiss的句子转换器。
Product search autocomplete implemented using keyword search and semantic search in Python. For keyword search, TheFuzz library is used and for semantic search Sentence-transformers with Faiss is used. (2024-02-26, Jupyter Notebook, 0KB, 下载0次)
使用K-means算法进行客户细分使用Logistic回归预测客户流失应用带交叉验证的朴素贝叶斯分类器增强客户流失预测
Segmented customers using K-means algorithm Predicted customers churn using Logistic Regression Applied Na ve Bayes classifier with Cross Validation to enhance customer churn prediction (2024-02-10, Jupyter Notebook, 0KB, 下载0次)
NLP项目提取文本数据，并训练朴素贝叶斯分类器模型，以从废弃的产品审查数据中预测积极或消极情绪。
NLP project to extract text data, and train a Na ve Bayes Classifier model to predict positive or negative sentiment from scraped product review data. (2024-02-06, Jupyter Notebook, 0KB, 下载0次)
我们提出了一种基于流形的自动编码器方法，用于学习具有Ricci流的流形潜空间的含时动力学，即PDE。
We present a manifold-based autoencoder method for learning time-dependent dynamics, namely PDEs, with a manifold latent space subject to Ricci flow. (2024-02-03, Jupyter Notebook, 0KB, 下载0次)
使用权重和偏差系统地调整和评估梯度提升分类器的超参数。我们正在使用的数据集是葡萄酒数据集。
Use of Weights & Biases to systematically tune and evaluate the hyperparameters of a Gradient Boosting Classifier. The dataset we are working with is the Wine dataset. (2024-01-31, Jupyter Notebook, 0KB, 下载0次)
深度学习中正交权重初始化和正则化的数学后果。在具有SeqMNIST数据集的RNN上使用增益调整正交正则化器的实验。
Mathematical consequences of orthogonal weights initialization and regularization in deep learning. Experiments with gain-adjusted orthogonal regularizer on RNNs with SeqMNIST dataset. (2024-01-27, Jupyter Notebook, 0KB, 下载0次)
基于Python的科学计算器由PyQt5构建，为数学、科学和工程领域的用户提供了支持标准数学运算和高级功能的用户友好界面。
The Python-based scientific calculator, built with PyQt5, provides a user- friendly interface supporting standard mathematical operations and advanced features for users in mathematics, science, and engineering. (2024-01-24, Jupyter Notebook, 0KB, 下载0次)
领域：机器学习|编程语言：Python|库：Pandas，NumPy，Seaborn，Matplotlib，Plotly|算法：线性回归（单个特征和多个特征），特征选择的标准缩放器
Domain: Machine Learning | Programming Languages: Python | Libraries: Pandas, NumPy, Seaborn, Matplotlib, Plotly | Algorithms: Linear Regression (single feature and multiple features), StandardScaler for Feature Selection (2023-12-20, Jupyter Notebook, 0KB, 下载0次)
Bob的Esti mate是在24小时ML AI黑客马拉松期间开发的预算优化器应用程序。使用XGBoost和随机森林回归，...
Bob s Esti-mate is a budget optimizer application developed during a 24-hour ML/AI hackathon. Using XGBoost and Random Forest regression, the app provides accurate estimates for construction materials (bricks, sand, cement), labor requirements, and project duration based on input square footage and the number of floors. (2023-11-24, Jupyter Notebook, 0KB, 下载0次)
我在Kaggle房价预测竞赛中的提交，在提交的前1%中名列前茅。这使用XGBoost回归器...
My submission to the Kaggle housing price prediction competition, placing in the top 1% of submissions. This uses the XGBoost Regressor, which implements gradient boosted decision trees with high speed and performance. (2021-08-19, Jupyter Notebook, 0KB, 下载0次)
在这个项目中，我们使用spark为6GB+的数据执行广告点击率（CTR）。我们构建了字符串索引器、标签字符串输入的管道...
In this project we performed Ads Click Through Rate (CTR) for 6GB+ data using spark. We Built a Pipeline of stringIndexers, labelstringIndxers and vectorAssembler to preprocess the data. Then we built your classification model using Gradient Boosting Tree model. (2019-10-04, Jupyter Notebook, 0KB, 下载0次)
使用XGBoost分类器通过梯度增强来预测InstaCart客户是否会在下次订单中再次购买商品...
Using XGBoost Classifier to Predict whether an InstaCart customer will purchase an item again in their next order using a gradient-boosting (XGBoost) machine learning algorithm. (2021-02-15, Jupyter Notebook, 0KB, 下载0次)
使用梯度Boosting分类器算法构建分类模型，并使用烧瓶框架、gunicorn和Heroku部署。
A classification model built using Gradient Boosting classifier algorithm and deployed using flask framework, gunicorn and Heroku. (2021-08-17, Jupyter Notebook, 0KB, 下载0次)
车辆诊断-使用手机传感器数据、ODB2车辆数据、摄像头信息的低成本硬件和开源算法，
Vehical Diagnostic - Low Cost Hardware and Open Source Algorithm using Mobile Phone Sensor Data, ODB2 Vehicle Data, Camera Information, (2022-12-24, Jupyter Notebook, 0KB, 下载0次)
滤波器（卡尔曼、霍德里克·普雷斯科特、移动平均）以及比较和灵敏度分析（在笔记本电脑中Filters_with_parameters...，
Filters (kalman, hodrick-prescott, moving average) together with comparison and sensitivity analysis (in notebook filters_with_parameters)+var analysis and granger causality test. Test for random walk (CE currencies using yfinance API) (2023-05-28, Jupyter Notebook, 0KB, 下载0次)
包含最常见的监督机器学习技术的NumPy实现的笔记本电脑集合-从简单的感知器到神经网络
Collection of notebooks containing NumPy implementations of the most common supervised machine learning techniques - from a simple Perceptron up to a Neural Network (2023-06-27, Jupyter Notebook, 0KB, 下载0次)
一个基于烧瓶的生产级web应用程序，使用朴素贝叶斯分类器来预测给定的SMS是垃圾邮件或火腿。还包括...
A Flask based production level web app which uses Naive Bayes classifier to predict given SMS is spam or ham. Also contains jupyter notebook with basic data exploration and ml modelling. (2018-12-27, Jupyter Notebook, 398KB, 下载0次)
该项目实现了使用线性最小二乘法训练的一对一和一对一二元分类器来分类...
This project implements a one vs. all and one vs. one binary classifier trained using linear least squares to classify digits 0-9. It also implements k-means clustering as an alternative for classification. (2020-11-28, Jupyter Notebook, 13942KB, 下载0次)