Includes top ten must know machine learning methods with R.
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Updated
Mar 6, 2024
Includes top ten must know machine learning methods with R.
Scikit-Learn compatible HMM and DTW based sequence machine learning algorithms in Python.
A data driven trade-bot, running on an ensemble of 3 different ML algorithms, generates buy/sell signals of a given asset and timeframe using technical indicators.
PCA(Principle Component Analysis) For Seed Dataset in Machine Learning
heart-disease analysis(Classification)
Data Science Project: SpaceX Falcon 9 First Stage Landing Prediction.
Portfolio
A simple python script that implements K Nearest Neighbors Algorithm. University Assignment
Modelo preditivo, baseado em 6 modelos de classificação binária e multiclasse, capaz de distinguir entre conexões "ruins", que são os ataques, das conexões "boas" ou normais.
I contributed to a group project using the Life Expectancy (WHO) dataset from Kaggle where I performed regression analysis to predict life expectancy and classification to classify countries as developed or developing. The project was completed in Python using the pandas, Matplotlib, NumPy, seaborn, scikit-learn, and statsmodels libraries. The r…
Syracuse University, Masters of Applied Data Science - IST 707 Data Analytics
CMS Hospital Rating with exploratory data analysis, data visualization, and applied machine learning predictive models, such as KNN, SVM, and Random Forest.
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.
Let's get those centroids!
Data Classification using K-Nearest Neighbour Classifier and Bayes Classifier with Unimodal Gaussian Density
The input for this task include gene-variation data and corresponding research text.
Classifier using supervised machine learning algorithm which can accurately predict whether or not the patients in the dataset have diabetes.
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