There are 0 repository under log-transformation topic.
Top 5th percentile solution to the Kaggle knowledge problem - Bike Sharing Demand
Image processing codes written in python
It is From Analytics Vidhya Hackathons, Sponsored by Club Mahindra. It is based on Regression Problem, Where Accuracy matters the most, It is measured by RMSE Score. Different Techniques such as Stacking, Ensembling, Boosting and Scientific Operations such box-cox Operations to reduce skewness of the data.
Various things, operation related to digital Image Processing
Image Processing Algorithms implemented from scratch with in-built concurrency support <3
This repository introduces reader to basic concepts of simple linear regression and its application.
This repo includes; Image Negative, Logarithmic Transformation, Power-Law (Gamma) Transformation, Averaging Filter, Median Filter, Laplacian Filter, Sobel Gradiant, Histogram Equalization, DFT, Marr and Hildreth, Otsu Thresholding, Global thresholding
Image Enhancement( Unsharp masking, Histogram Equalisation)
implement the concepts of Fourier Transformation technique such One-Dimensional Fourier Transform, Two-Dimensional Fourier Transform and Image Enhancement technique such as Image Inverse, Power Law Transformation and Log Transformation.
Udacity Data Scientist Nanodegree Project - Employ supervised algorithms to accurately model individuals income
Jupyter notebook and "Streamlit" python scripts for identifying features that can predict employee turn over rates at 250 senior care centers across the US. Combines multiple repetition of Lasso regression and linear regression. Integrates U.S. census data, employee salary, and employee tenure with data on employee satisfaction and engagement to improve the prediction accuracy and stability of the model.
Data Set: House Prices: Advanced Regression Techniques Feature Engineering with 80+ Features
Learn about Simple Linear Regression for Data Science
Predicting Delivery Time Using Sorting Time
Building a prediction model for Salary hike using Years of Experience
Modeling King County Home Prices via Multiple Linear Regression
It is a classification Problem where we are supposed to predict whether a loan would be approved or not.
Simple Linear Regression
Predicting Customer Response to Telemarketing Campaigns for Term Deposit. Output variable Whether the client has subscribed a term deposit or not.
Predict the Burned Area of Forest Fire with Neural Networks and Predicting Turbine Energy Yield (TEY) using Ambient Variables as Features.
Predict delivery time using sorting time and Build a prediction model for salary hike.
Data prepration and preprocessing for predictive modeling with SAS and Python
Prediction model for hourly bicycle utilization - task assignment
Analysis of Skewness and Kurtosis in Stock Return data and their Transformations
In this project, I utilized the RFM Model on the WonderfulWines dataset. As a noteworthy enhancement, I employed a log transformation to achieve greater data symmetry, which ultimately resulted in more accurate outcomes.
Image Processing Algorithms
Digital Image Processing (Java)
Introdução a técnicas de modelagem de dados para modelos de Regressão Linear utilizando StatsModels e Scikit Learn.
an R project of manipulating and fittingdata into regression with 95.5% R-Square, involving Automated Selection, detecting outliers, influential observations and multicollinearity
Detects sufficient and necessary conditions for pattern inversion conditional on log transform
Data Science - Simple Linear Regression Work
Spatial Data Science
Machine Learning Nano-degree Project : To identify customer segments hidden in product spending data collected for customers of a wholesale distributor
Feature engineering is the process of transforming raw data into features. Here are some basic ideas about feature engineering.