⚡机器学习实战(Python3):kNN、决策树、贝叶斯、逻辑回归、SVM、线性回归、树回归
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Updated
Oct 9, 2022 - Python
⚡机器学习实战(Python3):kNN、决策树、贝叶斯、逻辑回归、SVM、线性回归、树回归
Objective of the repository is to learn and build machine learning models using Pytorch. 30DaysofML Using Pytorch
Identify fraudulent credit card transactions so that customers are not charged for items that they did not purchase. (Python, Logistic Regression Classifier, Unbalanced dataset).
Customer Lifetime Value, Returns Predictions, Recommender system and sales analysis on UC Irvine online sales dataset.
A token is created to invest in long term volatility, which is very profitable in market crisis, but also in bull markets through algorithmic trading using an Adaboost machine learning model and VIXM.
Classification in TabularDataset
Analyse the factors which lead to online shopping on a website and building predictive models for it.
Classify default borrowers from initial loan application for Lending Club
Dtreehub is a lightweight decision tree framework for Python with categorical feature support. It covers regular decision tree algorithms: ID3, C4.5, CART, CHAID and regression tree, random forest and adaboost.
An algorithmic trading strategy incursion using Adaboost machine learning classifier, to create the first volatility security suitable for long term investors.
A parallelised facial recognition program written from scratch in C with minimal dependencies
Heart_Disease_Prediction
our goal for this project is to predict the churn probability of a customer using machine learning classification techniques.
Image classification using SVM, KNN, Bayes, Adaboost, Random Forest and CNN.Extracting features and reducting feature dimension using T-SNE, PCA, LDA.
For this project, I used four different classification algorithms to detect fraudulent credit card transactions.
Implementation of various machine learning algorithms from scratch.
This project is about to classify if an event is terrorist or other forms of crime as per the Global Standards.
Some decision tree algorithms implemented in C++
Ensemble methods is a machine learning technique that combines several base models in order to produce one optimal predictive model. To better understand this definition lets take a step back into ultimate goal of machine learning and model building. This is going to make more sense as I dive into specific examples and why Ensemble methods are u…
In This Repository you can find The Explanation and The Implementation of the Most Famous Machine Learning Algorithms
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