Design - Illustration Portfolio Website in White Black Light Experimental Style

GUNAL K

Machine Learning Engineer| Data Science intern

PORTFOLIO

A Little

About Me

Hello! I'm Gunal K, a passionate data enthusiast with a strong foundation in data analytics, machine learning, and data visualization. I thrive on solving complex problems and transforming raw data into meaningful insights. My journey in the world of data has been fueled by a curiosity to unravel patterns and make informed decisions.

Work Experience

INTERNSHIP :

TwiLearn EduTech Pvt. Ltd - Data Science Intern (01/12/22 - 01/02/23)

Gained practical experience in Python, data analysis libraries, and machine learning concepts.
Created interactive Power BI dashboards for data visualization.
Completed a project on heart disease analysis, applying Python and machine learning to create a predictive model using PCA & AdaBooster.

Acmegrade - Data Science Intern (07/10/22 - 07/12/22)

Learned and experienced fundamental and intermediate concepts required for the Data Science role using Python programming.
Completed a project on "The classification of Spam and Ham messages (Mail)."

Suvidha Foundation - Machine Learning Intern (13/10/22 - 13/11/22)

Learned Machine Learning concepts, NLP, Machine Learning libraries, and Python programming.

PwC (Forage) - Power BI Intern (05/05/22 - 03/10/22)

Gained real-time data experience, learned about Data Analytics and Data Visualization with Power BI tool.

AICL Training - Web Design (13/05/21 - 31/05/21)

Acquired knowledge of Web Designing using HTML, CSS, and JavaScript.

Skills & Expertise

Designer drawing with stylus on graphic tablet

SKILLS

Python (Programming & ML libraries)
Data analytics & Data science
Machine learning algorithms
HTML
CSS
SQL

TOOLS

Power Bi
IBM Cognos Analytics
COLAB

My PROJECT

1. Heart Disease Analytics Using PCA & AdaBooster

Utilized PCA to reduce dimensionality of heart disease-related data.
Implemented AdaBooster algorithm for classification, applied feature selection,

and engineered relevant features.

Evaluated model accuracy and performance metrics.

2. Estimate the Crop Yield Using Data Analytics

Analyzed agricultural data sets to predict crop yield using statistical modeling techniques.
Implemented predictive plots using IBM Cognos Analytics tools with IBM cloud.

3. Spam/Ham Email Classification Using NLP

Preprocessed email data for NLP analysis, developed an NLP model using TF-IDF and multinomial Naive Bayes.
Evaluated model performance metrics.

4. Tumor Detection Using Random Forest Classifier

Developed a tumor detection system using a random forest classifier on medical imaging data.
Preprocessed image data, extracted relevant features, and optimized classifier hyperparameters.

5. Weather Data and Predicting Precipitation Using Linear Regression

Analyzed historical weather data to predict precipitation levels using linear regression.
Conducted data cleaning, feature engineering, and developed a linear regression model.

6. EDA of COVID-19 and Happiness Index Using Python