Machine Learning C++
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Updated
Apr 29, 2023 - Jupyter Notebook
Machine Learning C++
人工智能检测恶意URL
Sentiment analysis of IMDB dataset.
Assumptions of Logistic Regression, Clearly Explained
This is repository about the MachineLaering Basics including all the Machine learning Algorithms
Assignment-06-Logistic-Regression. Output variable -> y y -> Whether the client has subscribed a term deposit or not Binomial ("yes" or "no") Attribute information For bank dataset Input variables: # bank client data: 1 - age (numeric) 2 - job : type of job (categorical: "admin.","unknown","unemployed","management","housemaid","entrepreneur","st…
Machine Learning algorithms from-scratch implementation. It covers most Supervised and Unsupervised algorithms. Homework assignments and Projects for graduate level Machine Learning Course taught by Dr Manfred Huber at UTA during Spring 21
Running a targetted marketing ads on facebook. The company wants to anaylze customer behaviour by predicting which customer clicks on the advertisement
This repository contains the Iris Classification Machine Learning Project. Which is a comprehensive exploration of machine learning techniques applied to the classification of iris flowers into different species based on their physical characteristics.
This project is to work on basic dataset to use logistic regression algorithm to classify which customer is going to buy the product.
Implementation of machine learning algorithms and evaluations on MNIST dataset.
Fire Incident risk classification Data Mining project
This is a sample code repository to leverage classic "Pima Indians Diabetes" from UCI to perform diabetes classification by Logistic Regression & Gradient Boosting algorithms.
A simple classification problem where SVM, Logistic Regression, KNN and Decision Trees algorithms are used and the F1-score with Jaccard similarity scores are found out.
Implementation of all basic algorithms needed in Deep Learning
Here we analysis the IPL Data set, and predict the accuracy apply different Machine Learning Algorithm
X Education needs a machine learning model which will increase their lead conversion beyond 80%. To solve this problem logistic regression model is developed which predicts a lead conversions up to 90% accuracy.
Build and evaluate various machine learning regression models using Python.
machine learning (logistic regression and other algorithm )
Logistic-Regression
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