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Achievement: Pair ExtraordinaireAchievement: Pull Sharkx2Achievement: QuickdrawAchievement: YOLO

Achievements

Achievement: Pair ExtraordinaireAchievement: Pull Sharkx2Achievement: QuickdrawAchievement: YOLO

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nabinelnino/README.md 
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║         B A G A L E  •  Software & Data Engineer             ║
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Typing SVG

LinkedIn Email GitHub

👨‍💻 About Me

I started writing code long before "vibe coding" existed. Back in my day, we actually understood what we were shipping — no AI autocomplete, no magic button, just raw logic, Stack Overflow, and sheer stubbornness. 🧠⚔️ (Still love you, Copilot. Don't tell anyone.)

I'm a Software & Data Engineer with deep roots in building scalable cloud-native data pipelines, full-stack web application, ML systems, and end-to-end AI solutions. My sweet spot is the messy intersection of data engineering, MLOps, and applied AI — turning terabytes of raw data into production-grade intelligence.

When I'm not wrangling data pipelines, I'm probably arguing about whether my football team deserved that result. ⚽

🧠 What I Actually Do

class NabinBagale:
    role       = ["Software Engineer", "Data Engineer", "MLOps Engineer"]
    cloud      = "GCP ☁️ (primary) | AWS | Azure"
    currently  = "Building AI/ML pipelines that actually make it to prod"
    learning   = "Always. Forever. There is no finish line."
    fun_fact   = "Started coding before 'vibe coding' was invented. OG debugger. 🪲"
    football   = "European football enjoyer 🏆 (the real football)"

🔬 Proud Project: AI/ML for Drug Discovery

Built a cloud-based AI/ML pipeline to predict hit discovery using DNA-Encoded Library (DEL) data.

  • 🧬 Processed hundreds of terabytes of molecular data
  • ⚙️ Delivered production-ready ML datasets and predictive models
  • 🔁 End-to-end pipeline: ingestion → processing → feature engineering → model training → serving
  • 🤖 Applied LLMs, RAG architectures, and classical ML in a real scientific context

Because why save data when you can save lives?

☁️ Cloud Stack

Platform Expertise Tools
GCP ⭐ Primary Deep BigQuery · Dataproc · Dataflow · Cloud Run · Pub/Sub
AWS Solid EC2 · S3 · Lambda · Glue · SageMaker
Azure Working ADF · Azure ML · Blob Storage · Databricks

🛠️ Tech Stack

🧑‍💻 Languages

Python TypeScript JavaScript SQL C#

🤖 AI / ML / Data

PySpark MLflow Airflow scikit-learn Pandas LLM

🌐 Web & Backend

Next.js React Node.js Django Flask

🗄️ Databases & Infra

PostgreSQL Redis Kafka Elasticsearch Cassandra Docker Kubernetes

📊 GitHub Stats

🤝 Let's Connect

I'm always open to collaborating on impactful data, ML, or AI projects — or just nerding out about football tactics.

LinkedIn Email

"In a world of vibe coders, be someone who actually reads the error message." 🧘‍♂️

Pinned Loading

  1. work-sample work-sample Public

    ETL pipeline and Data Analysis Project for Stock Data

    Python 1

  2. Audio-Emotion-Detection Audio-Emotion-Detection Public

    Audio emotion detection using Machine learning model

    Jupyter Notebook

  3. Disaster_Tweet_Analysis Disaster_Tweet_Analysis Public

    In this project a recurrent neural network is used to predict whether or not a tweet is talking about a real disaster or not

    Jupyter Notebook

  4. fast.api.app fast.api.app Public

    In this project I have created web based ML model which predicts 7-categories of images from Building, Forest, Glacier, Mountain, Sea, and Street with an accuracy of more than 85%. The web-based fi…

    Python

  5. Hyper-Parameter-Tuning Hyper-Parameter-Tuning Public

    Hyper Parameter tuning using CNN for Fashion MNIST dataset

    Jupyter Notebook

  6. Image-Classifier Image-Classifier Public

    The main goal of this Project is to create an image classifier from scratch using the Keras package. I have created binary classifier based on an object type of your choice. The classifier will acc…

    Jupyter Notebook