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 is a small simple linear regression project created for academic purposes.
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.
Linear Regression Machine learning The goal is to develop a model that can accurately predict salaries based on relevant features such as job title, years of experience, and education level.
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.
#️⃣ R, Linear Regression, Inferences, Correlation Analysis, Diagnosis, Remedial Measures,, Multiple Linear Regression, Quantitative and Qualitative Predictors, Logistic Regression and Poisson Regression, FIFA 18 Players Wages Prediction, HR Attrition at IBM Prediction. 🔢
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.
Developed Machine Learning models in Python to correctly Recognize handwritten letter and face images by training and later testing the models. The machine learning algorithms developed were Support Vector Machine, K- Nearest Neighbor and Nearest Centroid Classifier.
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.
PCA For Dimension Reduction And Visualization, Temperature-Yield Prediction Via Linear Regression, And Linear Fit Optimization Using Gradient Descent.
Predicting annual highest of sneakers on StockX
Explaining postoperative pain after mandibular third molar extraction.
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
Housing value predictive model (Using US official datasets to build predictive model by using excel)
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