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tbalani1 / repository
Used various Python libraries such as numpy, pandas, seaborn, matplotlib and scikit-learn on Jupyter notebook to analyze various factors influencing student grades by performing Exploratory Data Analysis (EDA) and implemented machine learning algorithm , Logistic Regression on “alcohol consumption on student grades”
Used various Python libraries such as numpy, pandas, seaborn, matplotlib and scikit-learn on Jupyter notebook to analyze various factors influencing student grades by performing Exploratory Data Analysis (EDA) and implemented machine learning algorithm , Logistic Regression on “alcohol consumption on student grades”
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renelikestacos /
Various examples for Google Earth Engine in Python using Jupyter Notebook
yrtnsari /
The project is a simple sentiment analysis using NLP. The project in written in python with Jupyter notebook. It shows how to do text preprocessing (removing of bad words, stop words, lemmatization, tokenization). It further shows how to save a trained model, and use the model in a real life suitation. The machine learning model used here is k-Nearest Neighbor which is used to build the model. Various performance evaluation techniques are used, and they include confusion matrix, and Scikit-learn libraries classification report which give the accuracy, precision, recall and f1- score preformance of the model. The target values been classified are positive and negative review.
sohilsshah91 /
This project gives an overview of crime time analysis in New York City . We have created Python Jupyter notebooks for spatial analysis of different crime types in the city using Pandas, Numpy, Plotly and Leaflet packages. As a second part to this analysis, we worked on ARIMA model on R for predicting the crime counts across various localities in the city based on correlations of various demographics correlation in each locality.
ksdkamesh99 /
The repository contains various python jupyter notebooks of predicting different medical diseases from various open source datasets.The following medical diseases predicted are cancer,,diabeties,kidney diseases,heart disease,liver diseases,spine disease using variou machine learning classification algorithms like KNN,Logistic Regression,Support Vector Machine,Decision Tree,Random Forest
sylligardos /
A hands-on tutorial on anomaly detection in time series data using Python and Jupyter notebooks. This repository includes interactive live-coding sessions, sample datasets, and various anomaly detection algorithms to provide a comprehensive learning experience.
PSO feature selection improves classifier performance. Implemented in Jupyter Notebook with pandas, numpy, scikit-learn. PSO done from scratch. Results compared using accuracy, precision, recall, F1 score. Improves results compared to using all features. Can be applied to various classification problems.