Suddala Srikar

<ul><li> Completed hands-on training in Data Analytics, Machine Learning, Deep Learning, NLP Generative AI, and Agentic AI, gaining practical experience in end-to-end machine learning workflows, including data preprocessing, EDA, feature engineering, model development, and evaluation. </li><li>Developed and evaluated classification and Regression models using Random Forest, XGBoost, LightGBM, Logistic Regression, and KNN, achieving up to 83% accuracy through feature engineering and hyperparameter tuning.</li><li> Designed and implemented end-to-end data analytics solutions using Python, SQL, Power BI, and SQL Data Warehouse, encompassing ETL pipeline development, data integration, predictive modeling, interactive dashboards, and analytics reporting.</li></ul>

<p>Mobile Price Analysis : Developed a Python-based web scraper using BeautifulSoup & Requests and Extracted mobile specifications (brand, model, RAM, storage, battery, price) from Flipkart and Cleaned and processed data using Pandas, NumPy & Regex and Handled missing values and performed data type conversions and Aggregated data from multiple pages into structured DataFrame and Conducted EDA to analyze pricing trends and brand comparisons.</p><p> • Tools & Technologies Used : Python, BeautifulSoup, Requests, Pandas, Numpy, Matplotlib, Seaborn, Regular Expressions (re), Web Scraping, Data Cleaning & Preprocessing, Data Visualization, Exploratory Data Analysis (EDA).</p><p> • Data Analysis of Men's Shirts on Flipkart : Developed a Python scraper using BeautifulSoup & Requests to extract product data from Flipkart and Cleaned and processed data with Pandas & NumPy, handling missing values and duplicates and Conducted exploratory data analysis and visualized insights via Matplotlib & Seaborn and Identified pricing outliers to prepare a refined dataset for further analysis. </p><p>• Tools & Technologies Used : Python, BeautifulSoup, Requests, Pandas, Numpy, Matplotlib, Seaborn, Regular Expressions (re), Web Scraping, Data Cleaning & Preprocessing, Data Visualization, Exploratory Data Analysis (EDA)</p>