Hi there, I'm Shailesh Kumar 👋!

• A Machine Learning / GenAI Engineer based in India.
• Working as Lead Data Scientist at Katonic AI.
• I love math, programming, data science, and books.
• Creator of ExplainIt, an opensource package for drift detection & data quality management.
• Open Source Enthusiast.
• See my portfolio at shaileshkumar97.github.io.

• Writing Python, SQL, HTML/CSS, PostgreSQL, MySQL, Redis etc...
• Contributing to Open Source.
• Mostly active on LinkedIn.
• Currently, building end-to-end production ready generative ai assistants/agents to handle different types of knowledge base for variety of usecases.
• Previously, built an end-to-end production pipeline for processing short videos with different usecases.

• 🎛 Machine Learning Operations (MLOps):

  • Language: Python • SQL
  • Framework: Mlflow • Kubeflow • Elyra • Dash • FastAPI • Streamlit
  • Databases: PostgreSQL • MySQL • Redis • Snowflake
  • Concepts: Data Pipeline • Feature Store • Data Governance • Model Pipeline • Model Deployment • App Deployment • Model Monitoring • Drift Detection • Model Explainability

• 👨‍💻 Python Developer:

  • Open Source Projects:

    • Explainit: A modern enterprise-ready business intelligence web application SDK for Drift Detection, Monitoring & Data Quality Management.

  • In-House SDK: (for katonic.ai)

    • Feature Store: To manage end-to-end life-cycle of features & integrate with existing data stores, feature pipelines, data governance, and ML platforms.
    • Connectors: To access the data from different databases/warehouses and stores to a given destination.
    • FileManager: To access, store and update/manipulate objects within the katonic file browser.
    • Pipeline: To convert an existing notebook into a Kubeflow pipeline.
    • AutoML: To build, Train & Log different Machine Learning, Deep Learning models.
    • Log: To quick register the trained models with mlflow in platform for deployment to the production environment.

• 🧮 Machine Learning:

  • Language: Python • SQL
  • Framework: Scikit-Learn • Xgboost • Catboost • Pandas • Plotly • Matplotlib • Pyspark
  • Databases: PostgreSQL • MySQL • PostgreSQL
  • Big Data: Spark • Data Lake (Delta, Hudi, Hive)
  • Protocol: REST

• 🤖 Deep Learning:

  • Language: Python
  • Framework: PyTorch • Tensorflow • Keras • OpenCV • Librosa

• 🗄️ Backend:

  • Language: Python
  • Framework: FastAPI • Flask • Streamlit, Dash
  • Databases: PostgreSQL • MySQL • AWS S3 • Redis • SnowFlake
  • System Architecture: Monolithic • Modular
  • Protocol: REST

• 🖥 Frontend:

  • Language: HTML • CSS • Python
  • Framework/Library: Dash, Streamlit
  • Utils: Bootstrap • Modular CSS

• 🎡 Ecosystem:

  • Containerization: Docker
  • Version Control: Git • GitHub
  • CI/CD: Github Actions
  • Project Management: GitHub Projects