Highly motivated and results-driven AI/ML Engineer with a strong foundation in Deep Learning, Natural Language Processing, and Computer Vision, currently pursuing an M.Tech in CSE. Proven ability to develop and deploy advanced machine learning models, evidenced by projects achieving up to 96% accuracy in image captioning, asteroid classification, and sarcasm detection. Eager to leverage expertise in predictive modeling, data analysis, and algorithm optimization to contribute to innovative AI solutions in a dynamic tech environment.
Bhopal, Madhya Pradesh, India
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Summary
Developed an asteroid classification model using the K-NN algorithm, achieving 95% accuracy by effectively managing multi-dimensional feature spaces for celestial data analysis.
Highlights
Implemented a K-Nearest Neighbors (KNN) algorithm for precise asteroid classification, achieving a 95% accuracy rate by leveraging multi-dimensional space analysis.
Managed complex multi-dimensional feature spaces to effectively integrate diverse asteroid characteristics, significantly enhancing the depth and accuracy of classification models.
Enabled improved analysis of celestial data through robust categorization, demonstrating strong data processing and pattern recognition capabilities.
Utilized Python and Deep Learning frameworks to develop and validate the classification model, showcasing proficiency in scientific computing.
Bhopal, Madhya Pradesh, India
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Summary
Led the development of an advanced image captioning system, integrating deep learning and computer vision techniques to achieve 96% descriptive accuracy and optimized model performance.
Highlights
Engineered an advanced image captioning system utilizing CNN, LSTM, and RNN architectures with context-based annotations, boosting descriptive accuracy by 96%.
Optimized data processing and feature engineering through efficient matrix operations, enhancing computational efficiency and model evaluation speed in machine learning workflows.
Integrated pre-trained deep learning models (VGG16, ResNet) for robust feature extraction, significantly reducing model training time and accelerating performance.
Applied principles of Natural Language Processing (NLP) to generate human-like image descriptions, demonstrating expertise in multimodal AI systems.
Bhopal, Madhya Pradesh, India
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Summary
Conducted comprehensive stock market prediction using advanced machine learning models and ensemble techniques to forecast price trends and inform strategic investment decisions.
Highlights
Analyzed historical stock market data with statistical methods and advanced ML models (Linear Regression, SVM, Neural Networks) to forecast price trends, guiding strategic investment decisions.
Enhanced prediction accuracy and mitigated overfitting by employing ensemble techniques like Bagging, Boosting, and Stacking, leading to more robust and reliable machine learning outcomes.
Utilized Jupyter Notebook, Python, and data visualization tools to present complex financial insights clearly and effectively.
Developed predictive models to support strategic investment decisions, demonstrating a practical application of machine learning in financial analytics.
Awarded By
Hackerrank / GeeksforGeeks
Achieved Rank 113 in Hackerrank in Python, GeeksforGeeks hackathon, and recognized in Geeks week-Locals and Python on Geeksforgeeks, demonstrating exceptional problem-solving and coding proficiency.
Published by
ResearchGate (inferred)
Summary
Designed and implemented a novel sarcasm detection model for social media, leveraging BERT embeddings and a hybrid ensemble of XGBoost and Random Forest to achieve 90% accuracy on Reddit data. Performed advanced NLP preprocessing and model tuning to enhance sentiment classification in short-text social media content.
Python, SQL, R, Java.
Keras, Caffe, Deep Learning, Machine Learning, CNN, LSTM, RNN, K-NN, BERT, XGBoost, Random Forest, Ensemble Learning, Predictive Modeling, Model Tuning, Feature Engineering.
Jupyter Notebook, Tableau, Data Visualization, Data Analysis, Statistical Methods, NLP (Natural Language Processing), Computer Vision, Algorithm Development.
R Studio, Linux, VS Code, Operating Systems.
HTML, CSS, JavaScript.
Cricket (State-level selection, 3-time Advitya champion), Kabaddi (State U16), Event Leadership (VIT University club events), Competitive Sportsmanship.