Completed 10th standard education with distinction from Tulsi Ram Maheshwari Public School, specializing in the PCM stream. Demonstrating strong analytical and Problem Skill Abilities
Graduated with distinction from Tulsi Ram Maheshwari Public School in 2021, specializing in the PCM stream. Acquired comprehensive knowledge and problem-solving skills.
Successfully completed a 3-month intensive training and internship program with Unified Mentor, specializing in fundamental Web development technologies like HTML, CSS, and Javascript
Currently enrolled in a 3-month training with Anudip Foundation, focusing on Python, SQL, and Machine Learning, with hands-on data analysis experience.
Successfully completed a 3-month intensive training and internship program with Unified Mentor, specializing in fundamental Web development technologies like HTML, CSS, and Javascript
Currently pursuing B.Tech in Computer Science and Engineering at Dr. K. N. Modi Institute of Engineering and Technology, with a keen interest in Web development to create dynamic and interactive websites.
Experienced in Python, TensorFlow, and scikit-learn, with strong skills in NumPy, Pandas, and Matplotlib for building models and visualizing data insights.
Built interactive AI apps with LLM models, LangChain, Hugging Face, and OpenAI API, delivering personalized, context-aware responses for a seamless user experience.
Skilled in video editing using Filmora and Canva. Capable of creating engaging visual content and enhancing audio quality for professional results.
Proficient in Git for version control and deployment using Vercel and Netlify. Skilled in frontend frameworks and browser developer tools for building and improving web applications.
Achieved 95.5% accuracy in predicting stroke risks using XGBClassifier, LightGBM, and RandomForest models.
Developed a model using Support Vector Machine (SVM) to predict Parkinson's disease, achieving 89% accuracy.
Implemented a model using Logistic Regression with TF-IDF Vectorization for effective feature extraction.
Implemented a model using Random Forest Classifier with Label Encoding for categorical data processing and Feature Scaling for optimal performance.
Implemented a model using K-Means Clustering with Principal Component Analysis (PCA) for dimensionality reduction and effective customer segmentation.
Implemented a model using Linear Regression with One-Hot Encoding for categorical variables and Feature Scaling for accurate medical cost predictions.
Built an LLM & Gen AI project using Llama 3.1 (LLM), Chromadb as a vector store, and LangChain for powerful processing.
eCommerce Sales Analysis using SQL and Python reveals customer insights and revenue trends with Jupyter Notebook visualizations.
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