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🌟 Python, R/Rstudio | 🤖 AI Development | 📈 Data Engineering | 📊 Data Analysis | 🧠 ML Model Training 🏆 Research Publications 👁️‍🗨️ Reproducing Repo Codebase - GitHub & Hugging Face ⏱️ Available across USA, Europe, UK, Australia, and preferred time zones 👋 Greetings, I help clients turn messy data into reliable Machine Learning models integration and deployment, Deep Learning pipelines, AI Research & Development solutions, and deployment-ready Python/R workflows. I work across Data Science, Data Analysis, Machine Learning, Deep Learning, AI, Computer Vision, NLP, Data Engineering, Web Scraping, Data Mining, LLMs, and R&D. Whether you need AI for research/development, Machine Learning for research/development, Deep Learning for research/development, or Data Analysis for business decisions, I can help you move from raw data to a working solution. 🎯 Core Services 📊 Data Science, Data Analysis & Statistics I clean, analyse, visualise, and explain complex datasets using Python, R/RStudio, SQL, Excel, dashboards, and statistical methods. I work on EDA, medical data statistical analysis, clinical data preprocessing, hypothesis testing, regression analysis, time series analysis, predictive analysis, survey analysis, financial analysis, research data visualisation, and business reporting. 🧠 Machine Learning & Model Training I build, fine-tune, evaluate, and optimise Machine Learning models for regression, classification, multi-class classification, forecasting, clustering, anomaly detection, churn prediction, sports data prediction, trading signals, risk scoring, recommendation systems, and business prediction. I focus on feature engineering, model training, model evaluation, explainable AI, and reproducible notebooks/scripts. 🏆 Research Support for ML & Deep Learning I support research-based Machine Learning, Deep Learning, AI, Computer Vision, NLP, and Data Science projects from idea to implementation. I can help from architecture design to final codebase. 🤖 AI Development, Deep Learning & Simulations I design and develop AI Development and Deep Learning solutions for research and development tasks, including AI/ML model fine-tuning, LLM fine-tuning, AI simulations, deep learning simulations, medical AI prototypes, epilepsy diagnosis models, sensor data modelling, multimodal AI, text-to-speech (TTS), text-to-image generation, model integration with web apps, and custom neural network pipelines. 👁️ Computer Vision, 2D/3D Data & Image AI I handle Computer Vision tasks across 2D image data, 3D data, video data, multi-camera data, medical images, satellite/geospatial data, and visual datasets. My work includes 2D image to 3D pose detection, 2D/3D pose estimation, 2D to 3D object modelling, image classification, image segmentation, object detection, object tracking, camera tracking, 3D inference, COLMAP workflows, and OCR data preparation. 💬 NLP, LLMs, RAG & Generative AI I work on text classification, embeddings, semantic search, RAG-based chatbots, LLM workflows, LLM fine-tuning, text mining, information extraction, document processing, chatbot development, and model integration with websites or web apps. 📈 Data Engineering, Scraping & Automation I build data collection, web scraping, website data extraction, data filtering, parsing, ETL, and automation workflows using websites, APIs, SQL databases, Excel/CSV files, and large structured datasets. I can scrape information from websites, clean sensor data, process sports data, mine data, structure raw files, and prepare datasets for Data Analysis, Data Science, Machine Learning, Deep Learning, AI Development, and Model Training. 👁️‍🗨️ Reproducing Repo Codebase - GitHub, Hugging Face If you have a research paper, GitHub repository, Hugging Face model, broken notebook, or incomplete codebase, I can reproduce, debug, modify, train, evaluate, document, and adapt it to your dataset. I can also fix dependencies and turn experimental code into a development-ready solution. ✅ What You Can Hire Me For ✅ Regression, classification, multi-class classification, forecasting, and prediction models ✅ Object detection, object tracking, image classification, and image segmentation ✅ 2D/3D pose estimation, 2D image to 3D pose detection, and 2D to 3D object modelling ✅ RAG-based chatbots, LLM fine-tuning, text classification, TTS, and text-to-image generation ✅ Trading bots, sports data, sensor data cleaning, clinical preprocessing, and medical AI ✅ Data cleaning, filtering, scraping, mining, ETL, dashboards, and research/business visualisation ✅ AI/ML model fine-tuning, AI simulations, Deep Learning simulations, and web model integration ✅ Research paper implementation and GitHub/Hugging Face repo 🌟 Why Work With Me? I focus on clean code, clear communication, practical delivery. You can send me a dataset, Excel/CSV file, database, API, sensor data, sports data, medical data, GitHub repo, Hugging Face model and I will turn it into a working solution.

𝐓𝐫𝐚𝐧𝐬𝐟𝐨𝐫𝐦 𝐘𝐨𝐮𝐫 𝐁𝐮𝐬𝐢𝐧𝐞𝐬𝐬 𝐰𝐢𝐭𝐡 𝐏𝐫𝐨𝐝𝐮𝐜𝐭𝐢𝐨𝐧-𝐑𝐞𝐚𝐝𝐲 𝐀𝐈 𝐒𝐨𝐥𝐮𝐭𝐢𝐨𝐧𝐬 | 𝟓𝟎+ 𝐏𝐫𝐨𝐣𝐞𝐜𝐭𝐬 𝐃𝐞𝐥𝐢𝐯𝐞𝐫𝐞𝐝 I am an AI/ML engineer specializing in end-to-end artificial intelligence development — from concept to deployed, scalable systems that solve real business problems. With 8+ years building machine learning, deep learning, and generative AI solutions for global clients (including Huawei and Turing), I deliver reliable, production-grade systems — not just prototypes. 𝐖𝐡𝐚𝐭 𝐒𝐞𝐭𝐬 𝐌𝐞 𝐀𝐩𝐚𝐫𝐭: ✓ Full-stack AI delivery: requirements → architecture → deployment → maintenance ✓ Battle-tested across 50+ international projects ✓ Focus on business impact, not just technical complexity ✓ Clear communication and rapid iteration cycles 𝐂𝐨𝐫𝐞 𝐓𝐞𝐜𝐡𝐧𝐢𝐜𝐚𝐥 𝐂𝐚𝐩𝐚𝐛𝐢𝐥𝐢𝐭𝐢𝐞𝐬: Computer Vision & Image Processing: Object detection | Image classification | ANPR systems | Face recognition | Video analytics | Image segmentation | OCR | Real-time tracking Natural Language Processing & LLMs: Chatbot development | RAG systems | LLM fine-tuning | Text generation | Sentiment analysis | Document summarization | Named entity recognition | GPT/Claude integration Audio & Speech Technologies: Automatic speech recognition (ASR) | Text-to-speech (TTS) | Speaker identification | Audio classification | Voice cloning | Noise reduction 𝐓𝐞𝐜𝐡 𝐒𝐭𝐚𝐜𝐤:Python | TensorFlow | PyTorch | Keras | Scikit-learn | Hugging Face | LangChain | OpenAI API | FastAPI | Flask | Docker | AWS | Azure 𝐃𝐞𝐥𝐢𝐯𝐞𝐫𝐲 𝐀𝐩𝐩𝐫𝐨𝐚𝐜𝐡:I take full ownership — understanding your use case, recommending the right approach, building the solution, and ensuring it works reliably in production. You get working software, comprehensive documentation, and post-deployment support. 𝐈𝐝𝐞𝐚𝐥 𝐅𝐨𝐫: Custom AI model development and training ML pipeline design and automation API development and third-party integration Proof-of-concept to production scaling Legacy system modernization with AI Let's discuss how AI can create measurable value for your business. Message me with your project details, and I'll respond with relevant examples and a clear path forward.

🌟 Top Rated Plus AI Engineer | PhD in Computer Science (AI, ML & Generative AI) I specialize in transforming complex ideas into scalable, real-world AI solutions that deliver measurable impact. With a strong blend of research excellence and practical implementation, I help businesses and researchers build intelligent systems that actually work in production. 🧠 Core Expertise 🔹 Computer Vision (YOLO, Vision Transformers, Object Detection) 🔹 Deep Learning (CNNs, Transformers, Vision Transformers - ViTs) 🔹 Generative AI & Large Language Models (LLMs) 🔹 NLP & Fine-tuning (BERT, LLaMA) 🔹 Predictive Modeling & Data Science 🔹Model Optimization & Deployment 💼 Featured Projects 🚧 AI-based Helmet Detection System (YOLOv8 + Vision Transformers) 🌱 Plant Disease Classification using Deep Learning 📉 Customer Churn Prediction System 🧾 Urdu NLP & LLM Fine-tuning Solutions 🏥 Medical Imaging with Explainable AI (Grad-CAM) 🎯 What I Can Do for You ✔ Design and develop custom AI/ML solutions tailored to your business ✔ Build Computer Vision systems (detection, classification, segmentation) ✔ Fine-tune and deploy LLMs & Generative AI applications ✔ Convert research papers into working, production-ready models ✔ Optimize models for performance, scalability, and deployment 🛠️ Tech Stack 💻 PyTorch | TensorFlow | OpenCV | Transformers | Python | Scikit-learn 💡 Why Choose Me? ✨ Top Rated Plus freelancer with a proven track record ✨ Strong PhD-level research + industry implementation expertise ✨ Clear communication, reliability, and on-time delivery ✨ Focus on building accurate, efficient, and production-ready AI systems 📩 Let’s collaborate to bring your AI idea to life! If you’re looking for a dependable expert in AI, Machine Learning, or Generative AI, I’d be happy to discuss your project. Regards 𝑫𝒓. 𝑺𝒂𝒏𝒂 𝑪𝒉𝒆𝒆𝒎𝒂

I am an educated data scientist & ML engineer who has worked in academia teaching Algorithms, machine learning and AI. I've been programming in python daily for over 3 years and that's where I do most of my data analysis. I have a lot of experience with machine learning and data visualizations, mainly in python. Working in a diverse set of fields has given me experience with many different types of data and obtaining it from many different sources. Some of the projects I have done are: • Computer Vision • Regression modeling • Machine learning and various statistical models in big data • Computer vision • Predictive Analytics • Natural Language Processing Tech stack: Keras, Python, SQL, TensorFlow, PyTorch, Scikit-learn, Spark, PennyLane

I am a Machine Learning Engineer with four years of experience working across deep learning research, large scale AI systems, and production model deployment. Over the years, I have worked extensively in medical imaging, computer vision, NLP, signal processing, and large language models, building systems that range from experimental research pipelines to deployed real world AI applications. My day to day work primarily involves Python, PyTorch, TensorFlow, Keras, HuggingFace Transformers, sentence transformers, scikit learn, OpenCV, Pandas, and NumPy. I enjoy working deeply on both the research and engineering sides of machine learning, especially problems that require understanding model behavior rather than simply applying existing architectures blindly. A large part of my background is research driven. I have authored multiple peer reviewed publications in indexed journals and IEEE conferences, including publications in Neurocomputing, Healthcare Analytics, Engineering Applications of Artificial Intelligence, Telematics and Informatics Reports, and other Elsevier and IEEE venues. My research has focused heavily on explainable AI, healthcare AI, and advanced deep learning systems. Some of my published work includes CARDxnosis, an explainable knowledge driven framework for ECG diagnosis and clinical report generation, an explainable AI system for trustworthy arrhythmia detection, a CNN RNN Attention hybrid architecture for automatic modulation classification, ensemble deep learning approaches for lung cancer detection from CT scans, and SRGAN based white blood cell image generation and classification pipelines. Alongside published work, I am currently involved in research on brain tumor segmentation, ADHD and ASD classification from brain connectome graphs, epileptic seizure prediction from EEG signals, and interpretable tabular learning using graph neural networks combined with Kolmogorov Arnold Networks. Beyond research, I have substantial hands on experience building and deploying production grade AI systems. One of my major recent projects was LaborBERT v4, a domain adaptive transformer fine tuning system processing hundreds of thousands of records through a large scale training pipeline. The project involved multiple experimental setups including contrastive learning, masked language model pretraining, temporal contrastive learning, cross attention based fusion, multi task training, and Matryoshka Representation Learning. I have also built hybrid embeddings plus LLM systems for taxonomy mapping using OpenAI embeddings alongside locally hosted LLaMA and Mistral models through Ollama. In addition, I have worked on deployed clinical AI systems and a portable on device diagnostic AI solution with embedded deep learning models for point of care inference, which gave me valuable experience in optimization, deployment constraints, inference design, and production reliability. My broader project portfolio includes vehicle detection using Mask R CNN, human activity recognition on the Kinetics 700 dataset, facial keypoint detection with MultiRes UNet, semantic segmentation pipeline redesign, Stable Diffusion based image editing workflows, toxic comment classification, RASA based conversational AI systems, and large scale scraping and automation pipelines using Playwright and Selenium. I have also worked with Flask and Django based deployment pipelines and cloud hosted ML systems. From an engineering perspective, I care strongly about clean and maintainable systems. I follow disciplined workflows involving modular code design, Git based version control, reproducible experimentation, structured evaluation, bootstrap validated metrics, and detailed documentation. I am also comfortable preparing scientific reports, research papers, and journal submissions using both LaTeX and Word. What ties all of this together is that I genuinely enjoy solving difficult technical problems, especially the kind that require balancing research depth with practical engineering constraints. I am most motivated by projects where thoughtful experimentation, careful system design, and real world usability matter equally.

I am junior data scientist and computer vision expert having 3 years of research experience during the research work of MS. Have good expertise in Python environment and data science domain. Have good understanding of Various AI techniques like Image classification, Image segmentation, prediction and clustering of data. Have good skill set in Data science libraries like Scikit-learn and Keras. Have good experience in computer vision and performed various computer vision tasks like features extraction as well as features matching using OpenCV.