babaniyi (Babs Olaniyi) · GitHub
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Achievement: Pull Sharkx3Achievement: Pair ExtraordinaireAchievement: StarstruckAchievement: YOLOAchievement: Quickdraw

Achievements

Achievement: Pull Sharkx3Achievement: Pair ExtraordinaireAchievement: StarstruckAchievement: YOLOAchievement: Quickdraw

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babaniyi/README.md

Hi, I’m Babs 👋

I build applied machine learning systems that help organizations make better decisions — whether that’s forecasting demand, defining product metrics, running experiments, or improving how resources are allocated.

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  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 24 4

  2. multimodal_llm_recsys_amazon multimodal_llm_recsys_amazon Public

    Multimodal LLM for Product Recommendation achieving 83.3% Hit Rate and 29% Precision. Combines GPT-2 with visual features (ResNet) for superior Amazon product recommendations, outperforming traditi…

    Python 2

  3. Deep-contextual-bandits Deep-contextual-bandits Public

    Deep contextual bandits in PyTorch: Neural Bandits, Neural Linear, and Linear Full Posterior Sampling with comprehensive benchmarking on synthetic and real datasets

    Python 12 1

  4. nuban_classifier nuban_classifier Public

    This Python project validates and classifies Nigerian bank accounts based on the Nigeria Uniform Bank Account Number (NUBAN) scheme.

    Python

  5. bandits bandits Public

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

    Jupyter Notebook

  6. BusinessML BusinessML Public

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

    Jupyter Notebook 1 1