1. Hospital Data Analysis:Their work focused on optimizing healthcare operations, improving patient outcomes, and providing actionable insights from complex medical data.2. LLMs Development and Fine-Tuning:They worked extensively on LLMs to build their in house chatbot, designing and fine-tuning state-of-the-art models.3. Search Solutions:They built and deployed advanced search systems, leveraging machine learning techniques to create efficient and intelligent retrieval solutions.

I have worked on a range of machine learning projects, including:1. Object Point Cloud Classification: Developed models to classify 3D point clouds using technique like PointNet, focusing on object recognition and spatial analysis.2. Face Recognition: Built deep learning models for facial feature extraction and recognition, leveraging CNNs and pre-trained models like FaceNet for real-time identification.3. Image Classification: Designed and implemented CNN-based models for classifying images across various domains, fine-tuning architectures like ResNet and EfficientNet for accuracy.4. Image Segmentation: Worked on semantic segmentation tasks using models like U-Net and Mask R-CNN to segment images for applications in medical imaging and autonomous driving.5. Text Classification: Developed text classification models using NLP techniques and frameworks like BERT, fine-tuning them for sentiment analysis, spam detection, and topic categorization.6. LLMs (LLama, ChatGPT): Implemented large language models (LLMs) like LLama and ChatGPT for tasks including text generation, summarization, and conversational AI, fine-tuning them to meet specific business needs.7. These projects involved end-to-end development, including data preprocessing, model training, fine-tuning, and deployment, with a strong focus on achieving high performance and accuracy in real-world applications.

As an ML Engineer Intern, I assisted in data preprocessing, model training, fine-tuning, and evaluation using tools like TensorFlow and PyTorch. I collaborated with senior engineers, contributed to deploying models, and applied the latest ML techniques to real-world projects.