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2 followers · 2 following
  • United States

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Achievement: Pull SharkAchievement: QuickdrawAchievement: YOLOAchievement: Arctic Code Vault Contributor
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Achievements

Achievement: Pull SharkAchievement: QuickdrawAchievement: YOLOAchievement: Arctic Code Vault Contributor
BetaSend feedback

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Pradyothsp/README.md

💫 About Me:

⌨️ I'm currently working on:
🎥 Large-scale fish video analysis using computer vision and deep learning
🐟 Achieving high accuracy in species identification and length measurement
🔭 Reducing manual effort by automating video processing with ML pipelines

👥 I'm looking to collaborate on:
🔓 Open-source machine learning projects
🕵️ Computer vision | 📖 Natural language processing | 📺 Recommender systems

🆘 I'm looking for help with:
⚡ Optimizing deep learning model performance and scalability
☁️ Deployment on cloud platforms (AWS, Azure)

📚 I'm currently learning:
🤖 Advanced deep learning (Vision Transformers, Large Language Models)
⚖️ Ethical and responsible AI development practices

💬 Ask me about:
🔧 Experience with data science tools (TensorFlow, PyTorch, PySpark)
🛒 Real-world applications (E-commerce, Computer Vision, Customer Analytics)

⚡ Fun fact:
🧠 Despite my technical background, I have a deep fascination for philosophy
🔭 Exploring societal implications of emerging technologies like AI

🌐 Socials:

LinkedIn Medium

💻 Tech Stack:

Programming Languages

Python R HTML5 Markdown LaTeX Shell Script

Web Development

Django Flask FastAPI DjangoREST JWT

Cloud & DevOps

Heroku AWS Azure Google Cloud Docker Apache Airflow

Big Data

Apache Kafka Apache Spark Apache Hadoop Apache Hive APACHEKAFKA

Databases

AmazonDynamoDB Couchbase Postgres Neo4J MySQL MongoDB SQLite

Machine Learning & Data Science

scikit-learn Scipy TensorFlow PyTorch Plotly Pandas NumPy Matplotlib Keras OpenCV

Tools & Utilities

Postman Notion Canva Gimp Bitwarden Anaconda

📊 GitHub Stats:



✍️ Random Dev Quote

Pinned

  1. backorder-prediction backorder-prediction Public

    This is a Django web application that uses machine learning to predict whether a product will go on backorder or not. It uses a pre-trained Random Forest Classifier, Decision Tree and LGBM models t…

    Jupyter Notebook 2

  2. person-detection-using-embarrassingly-parallel-computating person-detection-using-embarrassingly-parallel-computating Public

    This project aims to demonstrate the use of embarrassingly parallel computing techniques for detecting persons in video frames.

    Python 1

  3. Customer_Segmentation_Clustering Customer_Segmentation_Clustering Public

    This project aims to use k-means and Agglomerative clustering to segment customers into different groups based on their characteristics and purchasing habits. The goal is to understand the similari…

    Jupyter Notebook

  4. bd-pipeline bd-pipeline Public

    This project involves building a big data pipeline to source, process, and visualize data. The pipeline consists of multiple steps, including data sourcing using Python, Kafka for data streaming, A…

    Jupyter Notebook

  5. dv-world-energy-consumption dv-world-energy-consumption Public

    The "World Energy Consumption Visualized" project uses interactive visualizations to explore the dynamic connection between global energy consumption and economic prosperity, offering insights thro…

    JavaScript