Project 1
Project 1
Embedded Files
Underwriting Datamart
Underwriting Datamart
Worked for an Insurance-based client. We helped our client prepare Datamart which was used for Underwriting purposes. We used to write ETL Scripts in SQL to transfer Data from Oracle to Postgres.
Worked for an Insurance-based client. We helped our client prepare Datamart which was used for Underwriting purposes. We used to write ETL Scripts in SQL to transfer Data from Oracle to Postgres.
Related to - Infosys
Skills Used - SQL
1. Build Data pipelines and ETL scripts in SQL for Data Mart in Vertica.
1. Build Data pipelines and ETL scripts in SQL for Data Mart in Vertica.
2. Saved 10+ hrs. of weekly human time through automation using Python. Script compared Source
2. Saved 10+ hrs. of weekly human time through automation using Python. Script compared Source
and Target data to ensure smooth Migration of data from Oracle to Postgres.
and Target data to ensure smooth Migration of data from Oracle to Postgres.
Project 2
Project 2
Hybrid Intelligence
Hybrid Intelligence
Helped client gather Insights about competitor's research area, Tech on which competitors are publishing patents, and reviews of employees about the company and its competitors.
Helped client gather Insights about competitor's research area, Tech on which competitors are publishing patents, and reviews of employees about the company and its competitors.
Related to - PWC
Skills used - Python, Alteryx, Web Scrapping, PowerBI
Developed Web scrapper in python using beautifulsoup & requests_html to scrap Glassdoor & Indeed reviews & job postings.
Cleaned the Scrapped Data using Alteryx.
Data was used to Build a PowerBi report depicting the above requirements.
Project 3
Project 3
Credit Card Applicants Classifier
Credit Card Applicants Classifier
Built a Machine learning Classifier model for a leading bank. We used customer behavior history to classify users based on their eligibility for Credit Cards.
Built a Machine learning Classifier model for a leading bank. We used customer behavior history to classify users based on their eligibility for Credit Cards.
Related to - PWC
Skills used - Python,Machine Learning, Data Cleaning, SKlearn,Exploratory Data Analysis
Used Pandas for Data Cleaning.
Used Pandas and Seaborn for Exploratory Data Analysis to gain Insights about Data.
Feature Selection and Data preparation for ML model.
Tried different classification models. I was able to achieve 86% F1 score using XGBoost Model. The Model was used to decide whether users should be issued a credit card.
Grid Search is used for Hyperparameter Tuning.
Project 4
Project 4
Alteryx Macro
Alteryx Macro
Built an Alteryx Batch Macro to find Geospatial data about any location across the globe.
Built an Alteryx Batch Macro to find Geospatial data about any location across the globe.
Related to - PWC
Skills used - Alteryx
Built a Batch Macro which accepts column names containing locations using Control Parameter.
The Action Update tool is used to feed this information into the workflow.
It uses Bing API to fetch data from the Web.
We use Regex in Alteryx to split web fetched Information into columns.
The output of Macro is an Excel file that contains geospatial information like Latitude, longitude, state, city, country, etc.
Project 5
Project 5
Web Scrapping
Web Scrapping
The details of the books are expected to include the following data fields:
The details of the books are expected to include the following data fields:
['product_page_url', 'title', 'universal_product_code', 'price_including_tax', 'price_excluding_tax', 'number_available', 'category', 'review_rating']
['product_page_url', 'title', 'universal_product_code', 'price_including_tax', 'price_excluding_tax', 'number_available', 'category', 'review_rating']
Skills used - Python,Beautifulsoup
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Project 6
Project 6
Sentiment Analysis
Sentiment Analysis
We need to scrap tweets from popular hashtags. Sentiment Analysis is performed on these tweets to find out whether people think positively or negatively about those topics.
We need to scrap tweets from popular hashtags. Sentiment Analysis is performed on these tweets to find out whether people think positively or negatively about those topics.
Skills used - Python,nltk
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Project 7
Project 7
Exploratory Data Analysis
Exploratory Data Analysis
We need to perform exploratory Data Analysis to find Insights from Data and give data-driven business recommendations.
We need to perform exploratory Data Analysis to find Insights from Data and give data-driven business recommendations.
The market research team wants to identify the characteristics of the target audience for each type of treadmill offered by the company, to provide a better recommendation of the treadmills to new customers. The team decides to investigate whether there are differences across the product with respect to customer characteristics.
Perform descriptive analytics to create a customer profile for each treadmill product by developing appropriate tables and charts. For each treadmill product, construct two-way contingency tables and compute all conditional and marginal probabilities along with their insights/impact on the business.
The company collected data on individuals who purchased a treadmill from the stores during the prior three months.
Skills used: Python, Statistics, Exploratory Data Analysis.
Project 8
Project 8
Exploratory Data Analysis & CLT - Walmart
Exploratory Data Analysis & CLT - Walmart
The Management team at Walmart Inc. wants to analyze the customer purchase behavior (specifically, purchase amount) against the customer’s gender and the various other factors to help the business make better decisions. They want to understand if the spending habits differ between male and female customers: Do women spend more on Black Friday than men?
The Management team at Walmart Inc. wants to analyze the customer purchase behavior (specifically, purchase amount) against the customer’s gender and the various other factors to help the business make better decisions. They want to understand if the spending habits differ between male and female customers: Do women spend more on Black Friday than men?
Skills used: Python, Statistics, Exploratory Data Analysis.
Project 9
Project 9
Hypothesis Testing
Hypothesis Testing
Use Hypothesis testing to prove/disprove our hypothesis.
Use Hypothesis testing to prove/disprove our hypothesis.
We want to understand the factors affecting the demand for shared electric cycles in the Indian market.
Which variables are significant in predicting the demand for shared electric cycles in the Indian market?
How well do those variables describe the electric cycle demands?
Steps of Hypothesis testing:
Do usual exploratory data analysis steps like checking the structure & characteristics of the dataset.
Try establishing a relation between the dependent and independent variables.
Set up Null Hypothesis (H0) State the alternate hypothesis (H1) Check the assumptions of the test.
Set a significance level (alpha) Calculate test Statistics. The decision to accept or reject the null hypothesis.
Concepts Used:
Bi-Variate Analysis
2-sample t-test: testing for differences across populations
ANOVA
Chi-squared
Project 10
Project 10
Linear Regression
Linear Regression
The analysis will help in understanding what factors are important in graduate admissions and how these factors are interrelated among themselves. It will also help predict one's chances of admission given the rest of the variables.
The analysis will help in understanding what factors are important in graduate admissions and how these factors are interrelated among themselves. It will also help predict one's chances of admission given the rest of the variables.
Concepts Used:
EDA
Data Preprocessing(Duplicate value check,Missing value treatment,Outlier treatment,Feature engineering,Data preparation for modeling)
Check Assumptions for Linear Regression
Build linear regression model
Performence check for model.
Project 11
Project 11
Decision Trees & Grid Search
Decision Trees & Grid Search
Skills Used - Decision Tress, Random forest, Grid search
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