Need Python Jupyter Notebook assistance building predictive models
Budget: $1,500 – $3,000 USD
I have started a notebook in Python. The goal of the project is to estimate 4 target variables:
1. Sale Price of a house
2. Days on Market of a House
3. Whether a house will sell or not
4. % of listing price which the house will sell for
Additionally, I want to know which variables impact the target variable the most. Which have the most influence.
I have a jupyter notebook already made with linear regression, KNN and random forest applied but it needs some help. I need to make a few more models like multi-layer perceptron and others to see which model fits best. Once the model is made I need to use it on current listings in my area to see the predictions and continue to improve the model.
I have some of the data needed in order to input variables which I will supply. Data wrangling skills in Jupyter Notebook Python is very important. The rest of the data needed will have to be retrieved by scraping methods/Text mining.
Job description:
1. Create a Text Mining algorithm to find key words on property listings. These key words will be used as variables. I will provide the rest of the variables to you after that. Once all variables are collected you will use them to model.
2. Take the variables and Build several predictive models which will predict the 4 stated target variables above. Conduct pre-processing of data for missing values, outliers and wrong data. Create flag variables and standardize the variables. Conduct additional data wrangling as necessary to format the data properly for the model construction. After building the models using the training data, Fit it to a set of test data which I will provide also. Measure the performance and optimize the models. Provide the results and explain to me. Choose the best fitting model for each target variable prediction. The result should be 2 or 3 good predictive models which can be used any time I import new and relevant data. A script should be provided with all of the steps from start to finish. #Hashtag in notes which you think will be useful for me when reading the script.
Inquire now to learn more!
1. Sale Price of a house
2. Days on Market of a House
3. Whether a house will sell or not
4. % of listing price which the house will sell for
Additionally, I want to know which variables impact the target variable the most. Which have the most influence.
I have a jupyter notebook already made with linear regression, KNN and random forest applied but it needs some help. I need to make a few more models like multi-layer perceptron and others to see which model fits best. Once the model is made I need to use it on current listings in my area to see the predictions and continue to improve the model.
I have some of the data needed in order to input variables which I will supply. Data wrangling skills in Jupyter Notebook Python is very important. The rest of the data needed will have to be retrieved by scraping methods/Text mining.
Job description:
1. Create a Text Mining algorithm to find key words on property listings. These key words will be used as variables. I will provide the rest of the variables to you after that. Once all variables are collected you will use them to model.
2. Take the variables and Build several predictive models which will predict the 4 stated target variables above. Conduct pre-processing of data for missing values, outliers and wrong data. Create flag variables and standardize the variables. Conduct additional data wrangling as necessary to format the data properly for the model construction. After building the models using the training data, Fit it to a set of test data which I will provide also. Measure the performance and optimize the models. Provide the results and explain to me. Choose the best fitting model for each target variable prediction. The result should be 2 or 3 good predictive models which can be used any time I import new and relevant data. A script should be provided with all of the steps from start to finish. #Hashtag in notes which you think will be useful for me when reading the script.
Inquire now to learn more!