Praneeth A Email & Phone Number

Charlotte, Nc, Us

West Palm Beach, Florida, United States

• Conducted Named Entity Recognition task on Doctors – Patient Conversations, Dictation’s audio conversation data by implementing speech to text approach using amazon’s medical transcribe ML tool that uses machine learning by abiding HIPPA complaince. • Created a Docker Container for the react application by using nginx server in the file and deploying machine learning model application successfully on AWS ECS Fargate, S3, service for production.• Working on building a project that uses AI/ML.

North Carolina, United States

• Conducted research on a Biomedical Research Project on “ADHD detection in Sequential FMRI Brain Scans Data” using deep learning machine learning with improved performance.• Achieved 60% accuracy in ADHD detection by developing a deep learning model using Time-distributed-CNN – LSTM from tensorflow library architecture and performed hyper-parameter tuning and increased the accuracy of the model.• Performed research by Implementing Auto-encoder on gene data for cancer prediction and successfully increased the model's performance, yielding an impressive overall accuracy of 72%.

Bengaluru, Karnataka, India

• Conducted mining of email text data having Doctor and Patients’ health condition or General conversations and extracted useful information by NLP.• Performed "Context aware spell corrections" on text data by using "Spacy", "Spark" and "Nuespell" context spell checkers.• Implemented "Context aware expansions" on text data by "pycontractions" and expanded common English contractions in text.• Accomplished "Drugs and Diseases Named Entity Recognition" using "scispacy" and by string matching of drugs, diseases names from text with original ones by "Symspellpy" Spell Correction Algorithm after making n-grams of messages and identified drugs and diseases names from email conversationsdata.• Carried out Research on tracker algorithms and applied "Deepsort" on video frames data.

Hyderabad, Telangana, India

• Collaborated with a team of 7 individuals to engage in researchand development aimed at automating the process of assigningquestions with different levels of difficulty based on prior testresults, with the goal of enhancing students’ academicperformance.

• Performed Exploratory data analysis, data preprocessing, data visualization, feature engineering, predictive modelling and built a Supervised LGBM, and Deep Learning model, by using NLP to automate price suggestion of Mercari's Products using Regression. Developed a deep learning model to automatically recommend right product prices by predictive modeling and achieved an impressive error metric score of 0.42 after optimization.• Achieved 20% reduction time and leveraged scalability by running the model in GCP and Azure VM.• Developed machine learning model of CNN - LSTM model by training the machine learning model using the given Question-Article Pairs data to produce the short and long answer of a given question by predicting the start and end token indices of long and short answers from its pertaining article (Wikipedia) using NLP. Used BERT, GPT Transformer embeddings.• Built a model for sentiment analysis using Ensemble models and machine learning models achieving 85% accuracy using NLP. Experimented with various machine learning libraries and gained knowledge on several developments and tools in AI/ML by reading research papers. Performed fine tuning and optimization for better performance.

Master'S Degree, Computer Science, 3.64

Graduated with Master of Science degree in Computer Science (with a concentration in Data Science and Big Data & Machine Learning).

Bachelor Of Technology - Btech, Computer Science

Activities and Societies: Participated in Google Mobile Developer Fest. Participated in IOT Workshop. Participated in Ethical Hacking.

Intermediate, M.P.C