nikhilathota Goto Github PK
Name: Nikhila Thota
Type: User
Bio: Pursuing Data Science course in Springboard. Excellent in Data Analysis, Data Visualization, Statistics, Machine Learning, Python, SQL.
Location: Atlanta, GA
Nikhila Thota's Projects
boston_house_prices_linear_regression
Applied linear regression on Boston house prices data set to predict the sale price of a house.
capstoneproject_house_prices_prediction
Understand the relationships between various features in relation with the sale price of a house using exploratory data analysis and statistical analysis. Applied ML algorithms such as Multiple Linear Regression, Ridge Regression and Lasso Regression in combination with cross validation. Performed parameter tuning, compared the test scores and suggested a best model to predict the final sale price of a house. Seaborn is used to plot graphs and scikit learn package is used for statistical analysis.
classification_logistic_regression_
Logistic Regression in Python is used to study the classification problem of heights & weights in men and women
comparing_group_means
Compare the means of two groups (male & female) body temparatures
csbi_assignment
Data Exploration on a retail company. Python is for data manipulations and seaborn is used for exploration of data.
data_analysis_using_sql
Investigating a drop in user engagement of an organization -Yammer, with the help of advanced SQL queries and appropriate visualizations. Yammer_drop_users contains visualizations and SQL_queries file contains respective queries to extract data from multiple tables for analysis.
data_wrangling_json
Get familiar with Python packages for dealing with JSON
data_wrangling_xml
Transform XML tree structured file into data frame with Python pacakges
mini-projects
Data Wrangling
stat_analysis_recruiter_calls
Statistical Analysis is used to determine if race plays an important role in callback rates (from recruiters)
stats_analysis_hospital_readmissions
Used statistical measures to determine if the rate of re admissions for hospitals are high, if yes, what steps can be taken to bring the rate down.
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