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NeilBardhan/README.md

Hi, I'm Neil


I am an experienced Senior Machine Learning Engineer at Climate where I help build recommender systems and predictive models for farmers. My expertise lies in data engineering, model training and deployment, AI explainability, model monitoring, CI/CD and MLOps. I am also an experienced mentor to early career Data Scientists, Research Scientists and Software Engineers.

Skills and Expertise

  • Programming Languages: Python (pandas, numpy, matplotlib, scikit-learn, PySpark), R (dplyr, ggplot2, tidyverse), SQL, bash.
  • Machine Learning: Supervised Learning (Linear Models, Tree-based Models), Unsupervised Learning (Clustering, PCA).
  • Deep Learning: Neural Networks and CNNs (TensorFlow Probability, Keras, PyTorch), Natural Language Processing (NLTK, Gensim, LDA), SHAP ML explainability.

Frameworks

  • AWS: s3, EC2, ECR, SageMaker, IAM
  • GCP: GCS, BigQuery, Compute Engine, GKE, Vertex AI
  • Data Engineering: Apache Spark, Airflow, postgres, GraphQL
  • MLOps/DevOps: GitLab CI/CD, Docker, DataDog, Artifactory, GitHub Actions, MLFlow, Pydantic, FastAPI.
  • Product Management: JIRA, Confluence, Miro, Azure Dev Ops
  • Testing/Code Quality: pytest, black, SonarQube

Pinned Loading

  1. actions-cicd actions-cicd Public

    Learning about GitHub Actions' CI/CD capabilities

    Python

  2. data-engineering data-engineering Public

    Code repo for automating data pipelines and data engineering tasks

    Jupyter Notebook

  3. docker-latex docker-latex Public

    Docker build environment for building latex docs

    TeX

  4. gis gis Public

    Working with geospatial data in Python, R and QGIS

    HTML

  5. neilbio neilbio Public

    Code for neilb.io

    HTML

  6. technical-interview-prep technical-interview-prep Public

    Scripts to create a SQLite3 database for supporting Data Science technical interview practice in SQL and Pandas

    Jupyter Notebook