Rohit Mishra

Rohit Mishra - · @Email · @LinkedIn · @GitHub · @Unstop OBJECTIVE To apply my knowledge in computer technology and deep interest in artificial intelligence to create impactful AI solutions that address real-world challenges. I aspire to contribute to innovative AI research, improve machine learning systems, and grow as a professional in this dynamic field while continuously learning and adapting to emerging technologies. SKILLS & COMPETENCIES • Frameworks/Libraries: TensorFlow, Keras, Scikit-Learn, NLTK, Seaborn, Matplotlib, NumPy, OpenCV, Pandas, Flutter, Flask • Languages: Python, C++, Dart, SQL, R, HTML+CSS • Machine Learning: Neural Networks, Deep Learning, Supervised & Unsupervised Learning, NLP, Computer Vision, Model Deployment • Data Analysis: Data Visualization, Data Cleaning, Exploratory Data Analysis • Subject Knowledge: Linear Algebra, Calculus, Statistics • Other Tools & Techniques: Git, AWS, REST APIs PROJECTS Emotion Detection Application July 2024 - Dec 2024 Using Python and Google Collab Based on CONVOLUTIONAL NEURAL NETWORK (CNN) Developed a system to detect and classify emotions from input images into seven categories: Angry, Disgust, Fear, Happy, Neutral, Sad, and Surprise. Trained on a dataset of 30,000 images using a Convolutional Neural Network (CNN). Achieved an accuracy of 85% with a reduced inference time of ~150ms per image on a standard GPU. Technologies: Python, TensorFlow, Pandas, NumPy, OpenCV Email Spam Classifier Jan 2024 - June 2024 using Naive Bayes Classification and NLTK library Developed a machine learning model to classify emails as spam or non-spam using Natural Language Processing (NLP). Implemented text preprocessing techniques such as tokenization, stopword removal, and TF-IDF vectorization using the NLTK library. Trained the model using different Naïve Bayes classification algorithm and achieved 97.85% accuracy using Bernoulli NB and hyperparameter tuning. Deployed the model using streamlit. Technologies: Python, Scikit-Learn, NLTK, Pickle, Streamlit. Air Canvas System March 2023 - April 2023 Using OpenCV and Mediapipe Created a system using OpenCV and Mediapipe to enable object detection and hand gesture tracking, allowing users to draw on a digital screen with finger movements—without physical contact. The system achieves 88% accuracy in finger movement detection and includes features such as different drawing tools and a customizable color palette. Technologies: Python, OpenCV, Mediapipe, NumPy EDUCATION Bachelor’s In Computer Techonology 2022 - 2026 Specialization: Artificial Intelligence & Data Science Sage University, Indore CGPA - 8.2 Higher Secondary School Certificate - 12th 2021 Course: PCM Sita Devi Multi H.S. School, Palda, Indore Final Grade: 92 % Secondary School Certificate - 10th 2019 Vidya Bhavan Public School, Indore Final Grade: 92 % CERTIFICATIONS / HONORS Python(Basic) HackerRank - Issued September 2024 AWS Academy Graduate - AWS Academy Machine Learning Foundations Amazon Web Services (AWS) - Issued July 2023 AWS Academy Graduate - AWS Academy Cloud Foundations Amazon Web Services (AWS) - Issued June 2023 GOLD MEDAL - SCHOOL LEVEL IMO Olympiad - 2018, 2017 BRONZE MEDAL - SCHOOL LEVEL NSO Olympiad - 2017