Object Detection: Spearheaded dataset preparation, labelling, gathering, and filtering processes. Advanced the use of TensorFlow frameworks including TensorFlow Object Detection API, TensorFlow Model Maker, and Media-Pipe Model Maker, leading to a marked improvement in a currency detection model’s accuracy from 55% to 79%.Automation Initiatives: Developed an automated pipeline for image labelling utilising pre-trained models, which significantly reduced manual annotation efforts and increased processing speed.Document Detection Model: Created and refined a document detection model, enhancing its initial accuracy from 80% to 94% through strategic improvements in dataset quality and hyper-parameter tuning.PyTorch and Super-Gradient: Implemented training pipelines capable of handling all available Super-Gradient models for object detection and segmentation, incorporating a data filtering module to optimise dataset quality.Ultralytics Framework: Engineered a comprehensive data pipeline and scripting environment to facilitate the training of all models available within the Ultralytics framework, enhancing versatility and deployment readiness.Video Classification and Activity Detection: Developed a complete end-to-end training pipeline using MMAction2 for video classification and activity detection, significantly boosting model accuracy from 30% to 65% by transitioning from traditional LSTM techniques to pretrained MMAction2 models.Collaboration and Deployment: Collaborated closely with the Android development team to ensure the seamless integration and deployment of machine learning models into mobile platforms.Docker Utilisation: Managed various Docker containers to support application development and testing, ensuring robust and scalable deployment of machine learning applications.Client and Team Support: Routinely provided innovative solutions and expert advice to both clients and team members, facilitating ongoing project success and technological advancement.

As an AI intern I have extensively engaged in the development and Learning of both object detection models, employing advanced machine learning frameworks to significantly enhance performance and streamline operations across diverse applications.Researching on utilisation of frameworks like Tensorflow and cv2.Learn Feature engineering and dataset preparation , extraction and Filtering.Utilising Transfer learning for model training and testing.Conversion of models from base format to tflite fromat.

As an Camera vision intern i have learned to utilise computer vision for real world application and utilising the machine learning and deep learning models with computer vision and applied it to develop multi-framework utilising project and showcase the usage of these frameworks. Developed a multi-framework python script that utilise the machine learning models and cv2 to real time video analysis on sending alert for traffic assistant for pedestrians at traffic signals. Learned computer vision to utilise it for real time video processing. Utilising Raspberry -pi 4 for deploying and setting up the project script.

As a Trainee, I engaged in an intensive training program designed to provide foundational knowledge and skills in Machine Learning and Data Science. The training encompassed practical, hands-on experience, as well as theoretical learning, led by experienced professionals.Underwent comprehensive training in Machine Learning and Data ScienceParticipated in workshops and hands-on sessions to enhance practical skillsCollaborated with team members on various projectsReceived mentorship from experienced professionalsCompleted assignments and tasks under supervisionDeveloped understanding of industry standards and practicesPrepared and delivered presentations on assigned topicsEngaged in continuous learning and improvement activities

Work on basics of python fandamental and solving problems related to python basics and learning data science libraries (Numpy,pandas, matplotlib and scikit learn) in python, Also some basics of power bi and basic ML fundamentals.

Neo foundations an organisation that provides privilege to engineering students to test there expertise and be ahead and career advancement in there professional life's.