ML assignments from CSci 5525 at UMN
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Updated
Nov 4, 2017 - Jupyter Notebook
ML assignments from CSci 5525 at UMN
Hello! All codes belong to me. I created those codes for my Machine Learning Lab Class. Enjoy it!
Explanatory/Exploratory Data Analysis on FIFA19 dataset using hypothesis testing, confidence interval , Multiple Linear Regression
This project aims to develop a decision support system (DSS) to enhance Burger Bounty, a gourmet meatless burger food truck operating in the Hartford area. The system will aid the owner, in optimizing food truck sales and operations through data analysis and strategic recommendations.
Code for the exercises of the Machine Learning course offered by Stanford University on Coursera.
A linear regression model in Machine Learning
Deep Learning and Text Analysis: Compare Linear Regression and Neural Network Results
Sure Tomorrow used machine learning to tackle challenges. I assessed its efforts to identify clients for marketing, forecast the chance of new client claims, and ensure better predictive performance, all while safeguarding client privacy without affecting previous models.
A complete workshop on Machine Learning Algorithms
The challenge is to build a system that can quickly and accurately separate annoying spam emails from the important ones in your inbox. The goal is to make sure you only see the emails you want to see and avoid the hassle of dealing with unwanted or potentially harmful messages.
My first solo data science project! A simple project built using linear regression to predict box office success for movies using data I scraped myself.
Predicting annual highest of sneakers on StockX
Developed simple python program that implements Linear Regression on a sample dataset. The object of the class is declared and is fitted with the X_Train and Y_Train data. A graph is plotted using the matplotlib.pyplot to visually represent the Linear Regression model. The programuses sklearn.linear_model from the scikit-learn library to import …
A very simple Multiple Linear Regression (MLR) algorithm from Scratch. I did not use Scikit-Learn or any similar libraries
These are my notes, lessons, models, and code for topics on machine learning. Topics include everything from data pre-processing to logistic regression intuition, and more!
This project involves predicting Total Yield Energy of a gas turbine using linear regression models.
Machine learning project to distinguish between positive and negative reviews. Uses three classifiers: Naive Bayes, Support Vector Machine and Linear Regression Model.
The aim of our project is to analyze past years' bird strike data with respect to the phase of flight, time of day, pilot warning status, and various other parameters.
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