Greetings! I'm an accomplished Full Stack Machine Learning Engineer and Data Scientist with expertise in LLMs, Computer Vision Models, AR, and more. My skills span data collection, NLP, OpenAI models, generative AI, predictive analytics, and cloud technologies. I have a strong background in frameworks like PyTorch, TensorFlow, and HuggingFace, along with ETL tools and databases. I'm well-prepared to contribute to diverse projects and eager to discuss how I can bring value to your endeavors.
I am a full-time freelancer with a weekly availability of over 40 hours. I am consistently prepared to schedule meetings in accordance with the client's time zone preferences.
I specialize in several domains, including:
☑️ Data Collection, annotation, training of deep-learning models, inference, and deployment on clouds.
☑️ Computer Vision Models for Face Detection and Recognition, Pose Estimation, Object Detection, Segmentation, Stitching (Panorama Stitching), and Homography Warping
☑️ Natural Language Processing Models for Question Answering, Named Entity Recognition, Sentiment Analysis, Similarity Detection, Speech Text, Chatbots, Passage Re-Ranking, and Document Layout Token Classification Models
☑️ OpenAI's ChatGPT, GPT-4, LangChain, Pinecone, Vectara, Vectors Database, ElasticSearch, Large Text Analysis, Reports Summarization, Reports Generation, Long Book Question Answering Systems, Training and Deployment of LLMs including LLAMA-2, etc.
☑️ Building AI calling assistants by deploying all the models on own cloud infrastructure instead of using third party systems including training of all the models as per requirements.
☑️ Generative AI and GANs including super-resolution models, stability models, text-to-image, image enhancement, synthetic images/video/audio generation, voice cloning, text generation
☑️ Recommendation Systems based on watched/visited history, interest, search, popularity, and user-based and item-based recommendations
☑️ Predictive Analytics for Time Series Forecasting, Anomaly Detection, Root Cause Analysis, Key Performance Indicators (KPIs) development, Data Interpretations, and Hybrid Forecasting Models for improved accuracy
☑️ Data Visualizations in 2D and 3D using Matplotlib, Seaborn, Tableau, Pyrender, Open3D, Point Clouds, Affine and Projective Transformation of Images
☑️ Back-end development using Flask APIs, NodeJS, Laravel
☑️ Databases including MySQL, MongoDB, Cassandra, Redis, and Elastic Search
☑️ Deep-learning Frameworks: PyTorch, TensorFlow, HuggingFace, MMSegmentation, Spacy, NLTK, MediaPipe, AutoML, CoreML, MATLAB, and many open-source implementations on GitHub
☑️ Other Frameworks used in Machine Learning e.g. Scikit-Learn, XGBoost, OpenCV, NumPy, SciPy, SymPy, and Pandas
☑️ ETL Tools like WSO2 Streaming Integrator, Siddhi Scripting, Apache Kafka, Debezium Connectors, and Change Data Listeners (CDC)
☑️ Clouds including AWS Elastic Compute Cloud (EC2), Elastic Bean Stalk, Kubernetes (EKS), AWS Lambda Functions, AWS Sagemaker, S3 Storage, Google Cloud Platform, and Digital Ocean.
With my expertise, I can build large-scale, auto-scalable cloud architectures for heavy traffic applications. I have a strong understanding of mathematics, which helps me to improve model performance, image processing, transformations, and statistical analysis.