Harvard Project - Accuracy improvement by adding seasonality premium pricing
-
Updated
Dec 15, 2016 - Jupyter Notebook
Harvard Project - Accuracy improvement by adding seasonality premium pricing
Spark ML Dashboard built to plug-in and tweak the model params to real-time verify classification results on sample test data
All codes, both created and optimized for best results from the SuperDataScience Course
My implementation of homework 1 for the Introduction to Machine Learning class in NCTU (course number 1181).
This repository contains codes for running naive bayes and k-NN classification algorithms on large dataset in python
Kaggle competition (zillow housing challenge)for predicting housing price log errors.Used feature selection, feature engineering, ensemble and stacked models
Applied linear regression on Boston house prices data set to predict the sale price of a house.
Built a model to predict the value of a given house in the Boston real estate market using various statistical analysis tools. Identified the best price that a client can sell their house utilizing machine learning.
SKlearn K-fold implementation example
Understand the relationships between various features in relation with the sale price of a house using exploratory data analysis and statistical analysis. Applied ML algorithms such as Multiple Linear Regression, Ridge Regression and Lasso Regression in combination with cross validation. Performed parameter tuning, compared the test scores and s…
Creates a decision tree for training and predicts the targets!
Python and sklearn, KNN, logistic and linear regression, cross-validation
python scripts for analyzing gestures
Built a model to predict the value of a given house in the Boston real estate market using various statistical analysis tools. Identified the best price that a client can sell their house utilizing machine learning.
This is the code for "Binary Classification using Keras Sequential, Functional and Model Subclassing" By M.Junaid Fiaz
Add a description, image, and links to the k-fold topic page so that developers can more easily learn about it.
To associate your repository with the k-fold topic, visit your repo's landing page and select "manage topics."