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capstone

NYC Data Science Academy capstone project on multi classification of Lending Club data.

comcast-telecom-consumer-complaints

DESCRIPTION | Probllem Statement Comcast is an American global telecommunication company. The firm has been providing terrible customer service. They continue to fall short despite repeated promises to improve. Only last month (October 2016) the authority fined them a $2.3 million, after receiving over 1000 consumer complaints. The existing database will serve as a repository of public customer complaints filed against Comcast. It will help to pin down what is wrong with Comcast's customer service. Data Dictionary Ticket #: Ticket number assigned to each complaint Customer Complaint: Description of complaint Date: Date of complaint Time: Time of complaint Received Via: Mode of communication of the complaint City: Customer city State: Customer state Zipcode: Customer zip Status: Status of complaint Filing on behalf of someone

data-posit

healthcare-data-science-capstone

Problem Statement NIDDK (National Institute of Diabetes and Digestive and Kidney Diseases) research creates knowledge about and treatments for the most chronic, costly, and consequential diseases. The dataset used in this project is originally from NIDDK. The objective is to predict whether or not a patient has diabetes, based on certain diagnostic measurements included in the dataset. Build a model to accurately predict whether the patients in the dataset have diabetes or not. Dataset Description The datasets consists of several medical predictor variables and one target variable (Outcome). Predictor variables includes the number of pregnancies the patient has had, their BMI, insulin level, age, and more.

interview-guide

Java interview guide

nyc-customer-service-requests-analysis

DESCRIPTION | Background of Problem Statement¶ NYC 311's mission is to provide the public with quick and easy access to all New York City government services and information while offering the best customer service. Each day, NYC311 receives thousands of requests related to several hundred types of non-emergency services, including noise complaints, plumbing issues, and illegally parked cars. These requests are received by NYC311 and forwarded to the relevant agencies such as the police, buildings, or transportation. The agency responds to the request, addresses it, and then closes it. Problem Objective: Perform a service request data analysis of New York City 311 calls. You will focus on the data wrangling techniques to understand the pattern in the data and also visualize the major complaint types. Domain: Customer Service Analysis Tasks to be performed: (Perform a service request data analysis of New York City 311 calls) Import a 311 NYC service request. Read or convert the columns ‘Created Date’ and Closed Date’ to datetime datatype and create a new column ‘Request_Closing_Time’ as the time elapsed between request creation and request closing. (Hint: Explore the package/module datetime) Provide major insights/patterns that you can offer in a visual format (graphs or tables); at least 4 major conclusions that you can come up with after generic data mining. Order the complaint types based on the average ‘Request_Closing_Time’, grouping them for different locations. Perform a statistical test for the following: Please note: For the below statements you need to state the Null and Alternate and then provide a statistical test to accept or reject the Null Hypothesis along with the corresponding ‘p-value’. a) Whether the average response time across complaint types is similar or not (overall) b) Are the type of complaint or service requested and location related?