Customer Segmentation with Python
Built a K-Means Clustering Algorithm and Autoencoder for clustering the customers
ANJU PAUL
Data Scientist : Python | SQL | Tableau | Power BI | Machine Learning
PORTFOLIO
This section includes some of the works which I have done. It includes some projects that shows my skills and knowledge.
Let's predict whether you have diabetes or not?
A prediction model with visualization that tells whether a person has diabetes or not based on various parameters
Cleansing Data in SQL
The raw housing data is cleaned and transformed in SQL server for analysis
Smile Please...
My computer vision project to detect a smiling face using OpenCV
Sentiment Analysis Tool
A web app deployed in streamlit for the identification of the sentiment present in a text based on Artificial Neural Network
Drug Persistency
Data Science project that have large number of features to identify the persisitency of a drug
My Publications
A place where you can find my write ups
LLOYDS BANK DIGDATA CHALLENGE
Designed a data science process that predicts the likelihood of a new customer not paying back their loan using the historical data
G-2-M Advice
Data Analysis project to suggest the Go-To-Market strategy
Tokyo Olympics - An Analysis and visualization using Python
Exploratory Data Analysis of the 2021 Tokyo Olympics and visualization of the results
My Tableaue Projects
A combination of all my Tableaue Projects
Hi, I am Anju Paul.
My journey to a Data Scientist from an Oracle Database Administrator was not smooth. I had to set myself in the active-learning mode again after years of leaving the University.
Once started , It was so fascinating that I quit my 8+ years full-time job at Infosys and joined MSc Applied Data Science at Anglia Ruskin University, Cambridge, United Kingdom. I learned Python programming, Statistics, Research Methodology, Data Mining and Machine Learning. I am super proud that I completed the course with DISTINCTION, exactly 10 years after my previous graduation, competing with the young and fresh brains.
I learned more and more from free online courses, from various data scientists, and by doing projects. I have done an Internship at Data Glacier, where I have worked on different modules of company projects, proof of concepts using Python, Data Analysis, Machine Learning, Feature Engineering, Model Governance, Data Visualization, Model Deployment, and stakeholder communication.
It took a lot of passion, dedication, and constant striving toward the goal when having a career change or restarting after a career break.
I also write various articles on different topics in data science, they are quite simple and easy to understand for anyone. Do check out that as well.