Using Quantum Machine Learning to enhance Classification and Regression Machine Learning Models
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Updated
Jan 2, 2023
Machine learning is the practice of teaching a computer to learn. The concept uses pattern recognition, as well as other forms of predictive algorithms, to make judgments on incoming data. This field is closely related to artificial intelligence and computational statistics.
Using Quantum Machine Learning to enhance Classification and Regression Machine Learning Models
Machine learning models for discrimination of psychrophilic proteins
🤓📙Compilation of works of the master's degree in artificial intelligence
In this repository are covered some of the starters cases about Machine Learning.
Projects of practical machine learning and statistical learning that I did when studying in McGill University
This project aims to train a machine learning model to predict the price of a Peugeot 206 Type 2 car
Diabetes prediction using machine learning algorithms
Python for Machine Learning | Microsoft Student Summit 2023
predict The percentage of cancer by using classification: Support vector machines (SVM)
Using patient data as a csv file, I have built machine learning models to predict heart disease. Predictions involve:
論文『Machine Learning Phases Of Matter』の理解を目標にしたコード.
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This repository contains an example of a start-to-finish Machine Learning project and its files.
Machine Learning basics and operation process to manage the continous development, experiment and deployment.
This is a Machine Learning Project that uses various Machine Learning Algorithms to classify that whether a cell with certain features and characteristics is benign or malignant. I have used many classification algorithm( Supervised Machine Learning Algorithms) like Logistic Regression, Logistic Regression with Cross Validation, Decision Tree, Su
KNN Classifiers Implementation using anonymized data.
Binary classfication with scikit-learn and Random Forest models.
Trained ML model to predict employee promotion