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Achievement: StarstruckAchievement: YOLOAchievement: Pull Sharkx2Achievement: Quickdraw

Achievements

Achievement: StarstruckAchievement: YOLOAchievement: Pull Sharkx2Achievement: Quickdraw

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babaniyi/README.md

About Me

👋 Data Scientist & ML Engineer

I’m passionate about building scalable ML systems to solve real-world challenges. My work focuses on:

  • ⛵ Recommender Systems: Enhancing personalization.
  • 📊 Forecasting: Time-series analysis.
  • 📍 A/B Testing & Experimentation: Data-driven product improvements.
  • 📎 NLP + LLMs: Text-based insights and modelling.

📫 Connect: Website | LinkedIn

Skills

Category Skills
Programming Languages Python JavaScript Scala
Data Science and Statistics Scikit-learn Pandas Numpy Seaborn Matplotlib Pytorch
Machine Learning Libraries Keras TensorFlow Scikit-learn Pytorch Nltk
Frontend HTML5 Vue.js
Styling CSS3
Backend Flask FastAPI OpenAPI Django
MLOps and DevOps Git MLflow Docker GitHub Google Cloud

Pinned Loading

  1. LLMs-for-RecSys LLMs-for-RecSys Public

    Finetune a pre-trained GPT-2 model to generate personalized product recommendations for users, based on product reviews and metadata

    Python 16 3

  2. Deep-contextual-bandits Deep-contextual-bandits Public

    A benchmark to test decision-making algorithms for contextual-bandits. The library implements a variety of algorithms (many of them based on approximate Bayesian Neural Networks and Thompson sampli…

    Python 9 1

  3. bandits bandits Public

    Algorithms for multiarmed bandits such as e-greedy, thompson sampling, etc.

    Jupyter Notebook

  4. BusinessML BusinessML Public

    Using ML to solve business questions such as customer metrics, journey, growth and segmentation.

    Jupyter Notebook 1 1

  5. Metyis Metyis Public

    I provide a recommendation about the type of movies a film production company would have to do if the box takings and profit have to be maximized.

    Jupyter Notebook

  6. babaniyi babaniyi Public

    Github profile

    JavaScript