- 👨🏽🎓 I am a growing Artificial Intelligence (AI) Engineer. I am a motivated, talented, fast-learning, life-long learning, hard, and smart working professional. I believe that change is the only constant. In this bold era of the AI world, I'm constantly upgrading my real human intelligence and skills in technology, social, life, and my personality.
- I am from 🇮🇳, currently living in 🇳🇱
- 📧 If you would like to contact me, you can always reach me - abhishek.r.satyanarayana.4@gmail.com,
- HTSM_Oil_Spill_Segmentation Streamlit application has been deployed to HuggingFace
- image_colourization_CGAN FastAPI application has been deployed to HuggingFace with a streamlit frontend application HuggingFace
- Handwriting Recognition Flask application has been deployed to HuggingFace with a streamlit frontend application HuggingFace
- Cassava Leaf Disease Classification Flask application has been deployed to HuggingFace with a streamlit frontend application HuggingFace
- ML_water_potability FastAPI application has been deployed to HuggingFace
- overhead_mnist FastAPI application has been deployed to HuggingFace with a streamlit frontend application HuggingFace
- ML_multi_app_deployment is a project with multi-application deployment, a Streamlit frontend and a FastAPI backend
- Core skills - Computer Vision Algorithms, Machine Learning and Deep Learning Algorithms, MLOps, Model Optimization, Inference and Evaluation, Embedded / Edge ML, Containerization and Model Deployment, Data Pipelines, NLP, LLM, Data Science
- Programming languages - Python, C++, C, Matlab
- Packages and frameworks - Numpy, Pandas, Scipy, Scikit-learn, Scikit-image, Matplotlib, Seaborn, PyTorch, TensorFlow, OpenCV, Streamlit, FastAPI, Flask ....
- Version control (CI / CD) - Git, GitHub, GitLab
- Miscellaneous tech - Linux, TensorRT, MLFlow, Weights and Biases, Docker, Kubernetes, HuggingFace, Microsoft Azure, AWS, SQL, SQLite, MySQL
- ML on embedded computing hardware / edge devices - Raspberry Pi, Intel Movidius, Nvidia Jetson, Nvidia Xavier
- Interested in areas of Artificial Intelligence, Machine Learning, Deep Learning, Computer Vision, and Data Science.
- Playing badminton, playing chess, watching technology videos, listening to music, going for walks etc.