Karthikeya Reddy

My Forest Cover Type Prediction project used Python and machine learning to classify seven forest cover types from environmental and geographical features. I compared classification algorithms and achieved approximately 85.98% accuracy with Random Forest.

In an exploratory data analysis project, I cleaned a raw dataset by handling missing values, duplicates, inconsistent data types, and outliers. I used Pandas grouping and aggregation to summarize distributions and identify trends, then presented findings in tables and charts.

I’m completing the Certified Data Scientist program at DataMites®, where I’ve completed foundation work in data science, Python, and statistics. The program covers Python, SQL, machine learning, and BI tools.

My engineering background also includes a low-power FinFET D flip-flop design project, and I trained in IoT architectures and sensor networks. I’m targeting a junior Data Analyst, Junior Data Scientist, or Business / MIS Analyst role and am available to join immediately.