Set of Jupyter Notebooks on which I have worked Tools used for analysis and classifaction are: R programming language,Python programming language, Google Colab notebooks, numpy, matplotlib, sklearn, and matplotlib.
Attempt at Expolratory Data Analysis of the Cars Data Set in R
Worked on a custom dataset to predict winners of boardgame
Breast Cancer Classification using Support Vector Machine Models Exploring the Wisconsin Breast Cancer data set and using Support Vector Machine models to classify benign and malignant tumors.
In this project we will be using SVMs on the Wisconsin Breast Cancer dataset which can be found at the following URL:
https://archive.ics.uci.edu/ml/datasets/Breast+Cancer+Wisconsin+%28Original%29
This URL contains all relevant information on how the data is formatted. The data was collected by Dr. William H. Wolberg from the University of Wisconsin Hospital between 1989 and 1991. The dataset was never actually intended for any machine learning to be done on it, but you will be seeing how well you can get an SVM to classify the data.
Throughout the financial sector, machine learning algorithms are being developed to detect fraudulent transactions. In this project, that is exactly what we are going to be doing as well. Using a dataset of of nearly 28,500 credit card transactions and multiple unsupervised anomaly detection algorithms, we are going to identify transactions with a high probability of being credit card fraud. In this project, we will build and deploy the following two machine learning algorithms:
Local Outlier Factor (LOF) Isolation Forest Algorithm
DataSet:https://www.kaggle.com/mlg-ulb/creditcardfraud
Study of gene sequences Dataset:https://archive.ics.uci.edu/ml/machine-learning-databases/molecular-biology/promoter-gene-sequences/promoters.data
Analysis of Corona Virus Data