Categories
Computer Programming

Assignment instructions

IN498-2: System Specification: Design, implement, and evaluate an analytics-based solution to meet a given set of requirements in the context of the discipline.
Purpose
For this assignment, you will perform linear and logistic regression on a data set. You will apply the models to make predictions, or probabilities, based on installs versus 30-day retentions. You will also use data munging methods to add columns to better the model results.
You will use a single final CSV file that contains the contents of the nine provided data sets. Using the IN498_Unit3_student.py file, and the final CSV file, you will perform linear and logistic regression.
Assignment Instructions
You must have Python and PyCharm installed to perform this assignment. You should use the free editions for each.
If you do not have the above software installed, please perform the required installations. The following documents will assist you with installation of the software:
Python
PyCharm
Complete the following:
Please number the assignment items in your Microsoft Word document.
For items 1–7 below, provide a screenshot of the execution, in Python, showing the code and the result set. Be sure to submit the actual .py file. Make sure to also respond to items 8–11. Another possibility might be to copy and paste your code and results in the assignment document.
Start the next action on a new page.
If you have not done so, convert the provided raw data files into one final comma separated value (CSV) file with each data point having its own cell. This will be used for the linear and logistic regression analysis.
You will use the IN498_Unit3_Student.py file for this assignment.
Read the final CSV file into a data frame.
Explore the data set by performing the following steps:
Print the top 10 rows
Print the shape
Print the description
3. Replace NaN with 0 for Installers_retained_for_30_days.
4. Perform the below steps for linear regression:
Create a linear regression model
Set feature_cols to Installers column data only
Set X to feature_cols
Set y to installer retained for 30 days
Print the shape of X
Print the description of X
Print the shape of y
Print the description of X
Fit the linear regression model with X and y
Get predictions for retained for 30 days with 1 install
Get predictions for retained for 30 days with 2 installs
Get predictions for retained for 30 days with 4 installs
Print the intercept
Print the coefficient
5. Perform the below steps for logistic regression:
Get logistic regression model
Fit X and y to logistic regression model
Predict classes using X
Print the predictions using X
Get the predicted probabilities of class 1
Print the probabilities using X
Get probability for retained users for 30 days with 1 install
Get probability for retained users for 30 days with 2 installs
Get probability for ret ained users for 30 days with 4 installs
6. Using data munging techniques, perform the below steps on the data set:
Add a new column for installers retained for 30 days. Call it Install_30. If greater than 0, put 1, if 0, put 0
Print the top 10 rows of the new data set
Print the shape of the new data set
Print the description of the new data set
7. Using the new data set, complete the following for logistic regression:
Perform logistic regression using Install_30 column for y and X = Installers column
Fit X and y for logistic regression
Print the top 10 rows of X
Print the shape rows of X
Print the description of X
Print the top 10 rows of y
Print the shape of y
Print the description of y
Predict on X and capture the result to assorted_pred_class
Print the predictions using assorted _pred_class (X predictions)
Get the predicted probabilities of class 1 and save to assorted_pred_prob
Print the probabilities using assorted_pred_prob
Get probability for retained users for 30 days with 1 install
Get probability for retained users for 30 days with 2 installs
Get probability for retained users for 30 days with 4 installs
Print the intercept
Print the coefficient
8. Compare the probability results of the logistic regression models for both data sets. Explain the results.
What does the intercept values mean?
What does the coefficient values mean?
Summarize what the results are telling you based on the linear and logistic regression analysis.

Categories
Computer Programming

Provide a full apa reference entry at the end of the post.

Model Selection and Regularization Methods
Do some Internet or Library research beyond the text and find a credible resource that deals with model selection and regularization. Based on the resources, respond to the following for your initial post:
In paragraph form, summarize model selection and regularization as applied in data analytics. Include in your summary what shrinkage, dimension reduction, and principal component analysis are. Also include actual examples of where each method can be applied. Conclude your discussion with a table comparing the methods used for model selection and regularization.
For the initial post:
Cite your source properly using APA in-text citation.
Provide a full APA reference entry at the end of the post.
In responses to at least two others, consider sharing experiences about model selection and regularization or do some light research “beyond” the other student’s initial post (citing your sources, of course).

Categories
Computer Programming

Provide a full apa reference entry at the end of the post.

Do some Internet or Library research beyond the text and find a credible resource that deals with parsing CSV files using Python and Pandas. Based on the resources, respond to the following for your initial post:
In paragraph form, summarize the process it takes to parse a CSV file using Python. Use the example output below to guide your summary. Include in your summary how the CSV is input into a Pandas data frame and how the top 10 rows of a data frame are printed. Also, include actual Python code of how to read a CSV called IN499_Unit2.csv, create a Pandas data frame, and print the first 10 rows per the below columns. Conclude your discussion with the value of using the Pandas library for data analysis.
Date Installers
0 4/1/19 1.0
1 4/1/19 2.0
2 4/1/19 0.0
3 4/1/19 0.0
4 4/1/19 2.0
5 4/1/19 1.0
6 4/1/19 0.0
7 4/1/19 0.0
8 4/1/19 1.0
9 4/1/19 0.0
For the initial post:
Cite your source properly using APA in-text citation.
Provide a full APA reference entry at the end of the post.
In responses to at least two others, consider sharing experiences about parsing CSV files with Python and Pandas or do some light research “beyond” the other student’s initial post (citing your sources, of course).

Categories
Computer Programming

Provide a full apa reference entry at the end of the post.

Do some Internet or Library research beyond the text and find a credible resource that deals with data cleaning. Based on the resources, respond to the following for your initial post:
In paragraph form, summarize data cleaning. Include the five characteristics a data set should contain after cleaning: correctness, completeness, accuracy, consistency, and uniformity. Also, discuss methods used for data cleaning or munging, covering statistical methods, text parsing, and data transformations. Conclude your discussion with a conversation about which two characteristics and one method are most important and why.
For the initial post:
Cite your source properly using APA in-text citation.
Provide a full APA reference entry at the end of the post.

Categories
Computer Programming

Be sure to include the following:

Submit two files in the Assessment Dropbox. Be sure to include the following:
Word file with social issue description and URLs of three articles.
Plain Text file (.txt) contains 2000+ words from all three sources.

Categories
Computer Programming

Provide a full apa reference entry at the end of the post.

Do some Internet or Library research beyond the text and find a credible resource that deals with data cleaning. Based on the resources, respond to the following for your initial post:
In paragraph form, summarize data cleaning. Include the five characteristics a data set should contain after cleaning: correctness, completeness, accuracy, consistency, and uniformity. Also, discuss methods used for data cleaning or munging, covering statistical methods, text parsing, and data transformations. Conclude your discussion with a conversation about which two characteristics and one method are most important and why.
For the initial post:
Cite your source properly using APA in-text citation.
Provide a full APA reference entry at the end of the post.

Categories
Computer Programming

Be sure to include the following:

Submit two files in the Assessment Dropbox. Be sure to include the following:
Word file with social issue description and URLs of three articles.
Plain Text file (.txt) contains 2000+ words from all three sources.

Categories
Computer Programming

Add an attribute to media class to store indication when media object is rented versus available.

Instructions Attached Design and implement Java program as follows: 1) Media hierarchy: ? Create Media, EBook, MovieDVD, and MusicCD classes from Week 3 -> Practice Exercise – Inheritance solution. ? Add an attribute to Media class to store indication when media object is rented versus available. Add code to constructor and create get and set methods as appropriate. ? Add any additional constructors and methods needed to support the below functionality 2) Design and implement Manager class which (Hint: check out Week 8 Reading and Writing files example): ? stores a list of Media objects ? has functionality to load Media objects from files ? creates/updates Media files ? has functionality to add new Media object to its Media list ? has functionality to find all media objects for a specific title and returns that list ? has functionality to rent Media based on id (updates rental status on media, updates file, returns rental fee) 3) Design and implement MediaRentalSystem which has the following functionality: ? user interface which is either menu driven through console commands or GUI buttons or menus. Look at the bottom of this project file for sample look and feel. (Hint: for command-driven menu check out Week 2: Practice Exercise – EncapsulationPlus and for GUI check out Week 8: Files in GUI example) ? selection to load Media files from a given directory (user supplies directory) ? selection to find a media object for a specific title value (user supplies title and should display to user the media information once it finds it – should find all media with that title) ? selection to rent a media object based on its id value (user supplies id and should display rental fee value to the user) ? selection to exit program 4) Program should throw and catch Java built-in and user-defined exceptions as appropriate 5) Your classes must be coded with correct encapsulation: private/protected attributes, get methods, and set methods and value validation 6) There should be appropriate polymorphism: overloading, overriding methods, and dynamic binding 7) Program should take advantage of the inheritance properties as appropriate

Categories
Computer Programming

I have write university management project code on c++ in this code u can open teacher portal in which u put students marks.

I have write university management project code on c++ in this code u can open teacher portal in which u put students marks. I have made cafe portion and gaming zone also .

Categories
Computer Programming

All steps must be followed for this lab and just need a screen shot of the the l

ALL steps must be followed for this lab and just need a screen shot of the the last step showing it was completed