lenamax2355's starred repositories
sql-cookbook
Common SQL recipes and best practises
Fraud_Detection_SQL
Fraud Detection on credit card transations
ad_response_tutorial
This tutorial shows users how to evaluate advertising response using last click attribution, experiments, marketing mix models and attribution models. By applying these methods to the same (synthetic) data set, users will learn how the methods compare. We also illustrate the data manipulation that is required to prepare typical raw advertising data for analysis. Examples are worked in R and slides are provided in LaTeX.
SQL_Visual_Data_Analysis_of_Fraudulent_Transactions-
In this repo I have used SQL to analyze historical credit card transactions and consumption patterns in order to identify possible fraudulent transactions.
pandas_and_sql_example
This repo contains an example SQL database and using Python to answer questions.
fraudulent_charges_SQL
Using SQL to identify fraudulent credit card transactions.
CTR-Prediction
Click-through rate (CTR) is a very important metric for evaluating ad performance in online advertising. As a result, click prediction systems are essential and widely used for sponsored search and real-time bidding. In our dataset, we have provided 11 days’ worth of Avazu data to build and test prediction models.
healthcare_company_5_hour_takehome_test
A recent take home technical exam from a healthcare company I applied to. Rails API / ActiveRecord / SQL Business Analysis
Riot-Games-SQL-Assesment
This was the SQL Assesment and Pivot Table Test given to me for my interview with Riot Games
Using-SQL-To-Find-Fraud
Using SQL to analyze historical credit card transactions
sql_snippets
some query samples generating reports, BI optimized views, KPIs and Fraud alerts at Moburst
Business-Analyst-with-SQL
Business Analyst with SQL |Datacamp
220CTCoursework
This repository contains my work for the "Data and Information Retrieval" module in my 2nd year at Coventry University studying Bsc Computer Science. The tasks revolve around working with databases and Big Data. It contains questions regarding the use of SQL, the implementation of a database solution for a certain problem, the creation of a research poster on how Big Data helps fight fraud and a bigger and more creative task revolving around acquiring data and exploring it, with visualisation and coming up with ideas on how to productively use it.
Fraud_Detection
This is a project to implement a fraud detection model using random forests, postgres SQL, APIs, and Flask apps
Walmart_SQL_Assesment
Repository cantains output from SQL portion of Walmart take-home test