+91 (888) 681-4149 | [email protected] | https://github.com/rajeshkumarkarra | https://rajeshkarra.academia.edu | https://www.kaggle.com/rajeshkumarkarra
Dedicated and motivated recent graduate with a Bachelor's degree in Computer Science seeking an entry-level Machine Learning Engineer position to apply theoretical knowledge and develop practical skills in machine learning, deep learning, data science and Quantum Computing.
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House Price Predection | > Developed a machine learning model to predict house prices using a dataset of real estate listings. > Preprocessed data, performed feature engineering, and applied regression algorithms to achieve accurate predictions > Technologies Used: Python, scikit-learn, pandas, Matplotlib. - Sentiment Analysis with Deep Learning | > Implemented a sentiment analysis model using a deep learning architecture(LSTM) to classify movie reviews as possitive or negative. > Preprocessed text data, tokenized sentences, and created word embeddings for analysis. > Technologies Used: Python, TensorFlow, Natural Language Toolkit (NLTK). Hand written digit recognition | > Built a convolutional neural network (CNN) to recognize handwritten digits from the MNIST dataset. > Achieved high accuracy in digit recognition by optimizing model architecture and training parameters. > Technologies Used: Python, TensorFlow, Keras. > Intro to Machine Learning | Kaggle > Python | Kaggle > Pandas | Kaggle > Data Visualization | Kaggle > Intro to Programming | Kaggle > Data Cleaning | Kaggle > Proficient in English > German A1 > Available upon request |
> Physics/Quantum Computing: IBM Qiskit, FORTRAN, ROOT Library, Haskel
> Languages: Python, Java and C++ > Machine Learning Frameworks:TensoFlow, Scikit-learn, PyTorch > Data Manipulation and Analysis: Pandas, NumPy > Data Visualization: Matplotlib, Seaborn > Database: SQL > Version Control: GIT > IDEs: Jupyter notebook, VS Code > Supervised and Unsupervised > Deep Learning: Neural Networks, CNNs, RNNs > Natural Language Processing (NLP) > Computer Vision > Feature Engineering and Selection > Model Evalution and Hyperparameter Tuning > Data Processing and Cleaning > Cross-validation Techniques Machine > Problem Solving > Analytical Thinking > Team work and Collaboration > Communication Skills > Time Management > 2024 – B.Sc. Computer Science Osmania University, Hyderabad, TG - > Relevant Course work: Machine Learning, Deep Learning, Data Science, Algorithms, Data Structures, Statistics, Python, Java, C, C++. CGPA: 7.87 - > Final year Project: "Quantum optimization challenge - Get your starship out of a sticky situation!" This paper explores a unique application of the Traveling Salesman Problem (TSP) to optimize autonomous drone debris collection during a starship's perilous black hole approach. By framing the debris collection task as a TSP instance, we address the critical need for efficient, shortest-path solutions in a time-sensitive spacefaring scenario. Furthermore, we investigate the potential of IBM Quantum's QISKIT platform to solve this NP-complete problem, demonstrating the broader applicability of TSP and exploring the feasibility of quantum computing for real-world logistical optimization. |