Narendranath Kasarabada

With 2+ years of dedicated experience in Data Analysis preceded by 3 years of experience in sap domain, I have honed my skills and contributed significantly to roles such as IT Analyst, Application Development Analyst, and Associate Consultant at leading firms including TCS, Accenture, and Capgemini. My journey reflects a commitment to excellence in managing sap systems Through Data Analytics, implementing solutions, and ensuring seamless operations.

Sentiment Analysis :

Link:https://sentiment-pred.streamlit.app/

• Objective: Implementing sentiment analysis on user tweets to gain valuable insights into user opinions about a specific topic or service
• Positive and Negative Classification: The model accurately predicts whether a given text has a Positive or Negative sentiment with an accuracy of 87%
• Three-Class Prediction (Positive, Neutral, Negative): When extending to three classes (Positive, Neutral, Negative), the model maintains a good accuracy of 77%

K-means clustering visualization :

Link: https://kmeansviz.streamlit.app/

• This Project demonstrates a simple step-by-step cluster formation and displays the centroids of each cluster without using sk-learn library
• Deployed the model through GitHub by Leveraging Streamlit for a user- friendly web application, allowing easy interaction with the clustering results

Tableau Dashboard on Attrition Rate:

• This Dashboard explains the Attrition rate of employees by age, gender and education
• Link: https://public.tableau.com/app/profile/narendranarth.kasarabada/viz/HRAnalyticsdashboard_16967419680420/Dashboard1?publish=yes

Random Forests Regressor (without Sklearn) - Bias/Variance trade-off:

• The objective is to develop a robust Random Forest model that can effectively handle the model complexities by reducing the variance
• The model should provide accurate predictions.
• Link : https://github.com/naren579/Forever-Learner/tree/main/Random%20Forests

• NLP with Python
• Power BI for business
• Intelligence
• Time Series Analysis
• Advanced SQL Server for
• Data Analysis
• Python for DataScience