Acknowledgments
I sincerely thank my family who has supported me in my journey towards finishing my doctoral dissertation. I would first like to thank my Chair, Dr. Baird, Kelly D. I would like to express my gratitude to the rest of my dissertation committee. I am particularly thankful to Dr. John. Schwartz for invaluable assistance with the data analysis component of my dissertation. His expertise in quantitative and qualitative data research. I am grateful for the insightful comments and endless enthusiasm and positivity of my Reader, Dr. Arthur. Hendricks
Category: High School
To make a multiple quiz game (with buttons). This game contains logins for students so student id and password required. The students results from the quiz are put into a leaderboard where the teacher using a teacher login can view the students doing well. It needs to be a level standard so to include databases to store the results etc. Dont worry about the actual questions Ill put them
In so jus put in like one question to test it. Thanks
Hello I added the instructions to the order. But I would like to say that since I’m only in intro to Engineering don’t make the project too good since that would make them suspicious, just make it hit every requirement and keep it basic. Also one more thing is that I need the file to be compatible with Autodesk Inventor 2019. That’s all thanks.
When submitting an answer like 3540000000, you can type it in as is or using scientific notation like 3.54e9. If your answer is 0.00000542, you can also type it in like 5.42e-6.
Numerical answers must be typed to the most accurate value.
Numerical answers within 3% of the actual answer are counted as correct.
To avoid rounding errors in calculations, use at least three (3) significant figures for numerical answers.
I have attached my test for Advanced Functions and wanted the solutions to the questions. The question marks next to the questions indicate I have attempted the questions and wanted to know if my solutions were correct. Your answers can be written or typed whatever is easier and faster.
Make an algorithm
Given a set of points in plane, determine a rectangle with the smallest possible perimeter which contains all the points. The rectangle is not necessarily aligned with x or y axis.
For example:
a={(0, 0), (2, 1), (1, 2), (3, 3)}.
The smallest perimeter of rectangle is 8*sqrt{2}
Description
Thera Bank – Loan Purchase Modeling
This case is about a bank (Thera Bank) which has a growing customer base. Majority of these customers are liability customers (depositors) with varying size of deposits. The number of customers who are also borrowers (asset customers) is quite small, and the bank is interested in expanding this base rapidly to bring in more loan business and in the process, earn more through the interest on loans. In particular, the management wants to explore ways of converting its liability customers to personal loan customers (while retaining them as depositors). A campaign that the bank ran last year for liability customers showed a healthy conversion rate of over 9% success. This has encouraged the retail marketing department to devise campaigns with better target marketing to increase the success ratio with a minimal budget. The department wants to build a model that will help them identify the potential customers who have a higher probability of purchasing the loan. This will increase the success ratio while at the same time reduce the cost of the campaign. The dataset has data on 5000 customers. The data include customer demographic information (age, income, etc.), the customer’s relationship with the bank (mortgage, securities account, etc.), and the customer response to the last personal loan campaign (Personal Loan). Among these 5000 customers, only 480 (= 9.6%) accepted the personal loan that was offered to them in the earlier campaign.
Link to the case file:
Thera Bank_Personal_Loan_Modelling-dataset-1.xlsx
You are brought in as a consultant and your job is to build the best model which can classify the right customers who have a higher probability of purchasing the loan. You are expected to do the following:
EDA of the data available. Showcase the results using appropriate graphs – (10 Marks)
Apply appropriate clustering on the data and interpret the output(Thera Bank wants to understand what kind of customers exist in their database and hence we need to do customer segmentation) – (10 Marks)
Build appropriate models on both the test and train data (CART & Random Forest). Interpret all the model outputs and do the necessary modifications wherever eligible (such as pruning) – (20 Marks)
Check the performance of all the models that you have built (test and train). Use all the model performance measures you have learned so far. Share your remarks on which model performs the best. – (20 Marks)
Hint : split <- sample.split(Thera_Bank$Personal Loan, SplitRatio = 0.7)
#we are splitting the data such that we have 70% of the data is Train Data and 30% of the data is my Test Data
train<- subset(Thera_Bank, split == TRUE)
test<- subset( Thera_Bank, split == FALSE)
Please note the following:
Please note the following:
1. There are two parts to the submission:
1. The output/report in any file format – the key part of the output is the set of observations and insights from the exploration and analysis
2. Commented R code in .R or .Rmd
2. Please dont share your R code and/or outputs only, we expect some verbiage/story too – a meaningful output that you can share in a business environment
3. Any assignment found copied/ plagiarized with other groups will not be graded and awarded zero marks
4. Please ensure timely submission as post-deadline assignment will not be accepted
Thanks
Description
Thera Bank – Loan Purchase Modeling
This case is about a bank (Thera Bank) which has a growing customer base. Majority of these customers are liability customers (depositors) with varying size of deposits. The number of customers who are also borrowers (asset customers) is quite small, and the bank is interested in expanding this base rapidly to bring in more loan business and in the process, earn more through the interest on loans. In particular, the management wants to explore ways of converting its liability customers to personal loan customers (while retaining them as depositors). A campaign that the bank ran last year for liability customers showed a healthy conversion rate of over 9% success. This has encouraged the retail marketing department to devise campaigns with better target marketing to increase the success ratio with a minimal budget. The department wants to build a model that will help them identify the potential customers who have a higher probability of purchasing the loan. This will increase the success ratio while at the same time reduce the cost of the campaign. The dataset has data on 5000 customers. The data include customer demographic information (age, income, etc.), the customer’s relationship with the bank (mortgage, securities account, etc.), and the customer response to the last personal loan campaign (Personal Loan). Among these 5000 customers, only 480 (= 9.6%) accepted the personal loan that was offered to them in the earlier campaign.
Link to the case file:
Thera Bank_Personal_Loan_Modelling-dataset-1.xlsx
You are brought in as a consultant and your job is to build the best model which can classify the right customers who have a higher probability of purchasing the loan. You are expected to do the following:
EDA of the data available. Showcase the results using appropriate graphs – (10 Marks)
Apply appropriate clustering on the data and interpret the output(Thera Bank wants to understand what kind of customers exist in their database and hence we need to do customer segmentation) – (10 Marks)
Build appropriate models on both the test and train data (CART & Random Forest). Interpret all the model outputs and do the necessary modifications wherever eligible (such as pruning) – (20 Marks)
Check the performance of all the models that you have built (test and train). Use all the model performance measures you have learned so far. Share your remarks on which model performs the best. – (20 Marks)
Hint : split <- sample.split(Thera_Bank$Personal Loan, SplitRatio = 0.7)
#we are splitting the data such that we have 70% of the data is Train Data and 30% of the data is my Test Data
train<- subset(Thera_Bank, split == TRUE)
test<- subset( Thera_Bank, split == FALSE)
Please note the following:
Please note the following:
1. There are two parts to the submission:
1. The output/report in any file format – the key part of the output is the set of observations and insights from the exploration and analysis
2. Commented R code in .R or .Rmd
2. Please dont share your R code and/or outputs only, we expect some verbiage/story too – a meaningful output that you can share in a business environment
3. Any assignment found copied/ plagiarized with other groups will not be graded and awarded zero marks
4. Please ensure timely submission as post-deadline assignment will not be accepted
Thanks
Scoring guide (Rubric) – Project 4
Criteria Points
1. EDA – Basic data summary, Univariate, Bivariate analysis, graphs 10
2.1 Apply Clustering algorithm < type, rationale> 5
2.2 Clustering Output interpretation < dendrogram, number of clusters, remarks to make it meaningful to understand> 5
3.1 Applying CART <plot the tree> 5
3.2 Interpret the CART model output <pruning, remarks on pruning, plot the pruned tree> 5
3.3 Applying Random Forests<plot the tree> 5
3.4 Interpret the RF model output <with remarks, making it meaningful for everybody> 5
4.1 Confusion matrix interpretation 5
4.2 Interpretation of other Model Performance Measures <KS, AUC, GINI> 10
4.3 Remarks on Model validation exercise <Which model performed the best> 5
Points 6
Description
Thera Bank – Loan Purchase Modeling
This case is about a bank (Thera Bank) which has a growing customer base. Majority of these customers are liability customers (depositors) with varying size of deposits. The number of customers who are also borrowers (asset customers) is quite small, and the bank is interested in expanding this base rapidly to bring in more loan business and in the process, earn more through the interest on loans. In particular, the management wants to explore ways of converting its liability customers to personal loan customers (while retaining them as depositors). A campaign that the bank ran last year for liability customers showed a healthy conversion rate of over 9% success. This has encouraged the retail marketing department to devise campaigns with better target marketing to increase the success ratio with a minimal budget. The department wants to build a model that will help them identify the potential customers who have a higher probability of purchasing the loan. This will increase the success ratio while at the same time reduce the cost of the campaign. The dataset has data on 5000 customers. The data include customer demographic information (age, income, etc.), the customer’s relationship with the bank (mortgage, securities account, etc.), and the customer response to the last personal loan campaign (Personal Loan). Among these 5000 customers, only 480 (= 9.6%) accepted the personal loan that was offered to them in the earlier campaign.
Link to the case file:
Thera Bank_Personal_Loan_Modelling-dataset-1.xlsx
You are brought in as a consultant and your job is to build the best model which can classify the right customers who have a higher probability of purchasing the loan. You are expected to do the following:
EDA of the data available. Showcase the results using appropriate graphs – (10 Marks)
Apply appropriate clustering on the data and interpret the output(Thera Bank wants to understand what kind of customers exist in their database and hence we need to do customer segmentation) – (10 Marks)
Build appropriate models on both the test and train data (CART & Random Forest). Interpret all the model outputs and do the necessary modifications wherever eligible (such as pruning) – (20 Marks)
Check the performance of all the models that you have built (test and train). Use all the model performance measures you have learned so far. Share your remarks on which model performs the best. – (20 Marks)
Hint : split <- sample.split(Thera_Bank$Personal Loan, SplitRatio = 0.7)
#we are splitting the data such that we have 70% of the data is Train Data and 30% of the data is my Test Data
train<- subset(Thera_Bank, split == TRUE)
test<- subset( Thera_Bank, split == FALSE)
Please note the following:
Please note the following:
1. There are two parts to the submission:
1. The output/report in any file format – the key part of the output is the set of observations and insights from the exploration and analysis
2. Commented R code in .R or .Rmd
2. Please dont share your R code and/or outputs only, we expect some verbiage/story too – a meaningful output that you can share in a business environment
3. Any assignment found copied/ plagiarized with other groups will not be graded and awarded zero marks
4. Please ensure timely submission as post-deadline assignment will not be accepted
Thanks
Program Office
Scoring guide (Rubric) – Project 4
Criteria Points
1. EDA – Basic data summary, Univariate, Bivariate analysis, graphs 10
2.1 Apply Clustering algorithm < type, rationale> 5
2.2 Clustering Output interpretation < dendrogram, number of clusters, remarks to make it meaningful to understand> 5
3.1 Applying CART <plot the tree> 5
3.2 Interpret the CART model output <pruning, remarks on pruning, plot the pruned tree> 5
3.3 Applying Random Forests<plot the tree> 5
3.4 Interpret the RF model output <with remarks, making it meaningful for everybody> 5
4.1 Confusion matrix interpretation 5
4.2 Interpretation of other Model Performance Measures <KS, AUC, GINI> 10
4.3 Remarks on Model validation exercise <Which model performed the best> 5
Points 6
This is Grade 10 work only. (class ICS2O, Canada)
Negotiations on price may be allowed depending on the work you offer!
Only need minimum 60% of this done.
These are the instructions I was given https://pastebin.com/trGAsW4M
rubric: https://snipboard.io/fFyEw7.jpg (proposal/worklog not needed)
I had an idea for a crossyroad/frogger style 2d top down game
I only require a few levels (or random generation system)
Mainly just need the basic code, you don’t need to make it look great.
External assets (e.g. images) are allowed
