CHARAN TEJA VEDICHERLA

Dynamic software developer with a proven track record at Tech Solutions, excelling in Python and Java. Recognized for enhancing web applications through HTML and CSS, leading to a 30% increase in user engagement. Strong problem-solving skills and a collaborative spirit drive successful project outcomes.

Ultimate big data masters program

REAL TIME TRAFFIC SIGN PREDICTION

2023

Real-time traffic sign prediction uses cameras to capture road video, processes frames to detect and classify signs using computer vision and machine learning, and then uses the information for driver assistance or autonomous driving. Key technologies include convolutional neural networks (CNNs) for detection, which are robust to variations in lighting and weather. Advanced methods like Faster R-CNN can be used for more complex tasks like bounding box regression and classification.

NIFTY STOCK MARKET ANALYSIS USING ENSEMBLE CLASSIFICATION

2025

• Developed a predictive model for Nifty 50 stock price movements using advanced ensemble classification methods (e.g., Random Forest, Gradient Boosting, Stacking).
• Analyzed and pre-processed extensive financial time-series data, including historical prices, trading volumes, and technical indicators (e.g., RSI, MACD, Bollinger Bands).
• Implemented and evaluated various ensemble learning strategies, such as bagging, boosting, and stacking, to enhance prediction accuracy and model stability.
• Achieved a high classification accuracy (e.g., "up to 90%" or the specific metric you achieved) in forecasting daily stock trends, demonstrating the effectiveness of ensemble techniques in a non-linear market.
• Utilized Python libraries (e.g., Pandas, Scikit-learn, NumPy, Matplotlib) for data manipulation, model development, and results visualization.
• Applied data cleaning and feature engineering techniques to manage noise and uncertainty inherent in stock market data, improving the robustness of the predictive model.
• Gained a deep understanding of stock market dynamics and the application of machine learning for fundamental and technical analysis to inform investment decisions.