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The objective of this study is to explore the impact of the structure of a Bayesian Network on its overall run-time, potential unwanted bias, and accuracy in performing a classification task. A credit card default dataset was utilised to construct six networks with varying structures and to learn their conditional probability distributions.

License: MIT License

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bayesian-network pgmpy python credit-card-dataset

bayesian-network-credit-cards's Introduction

Hello there! ๐Ÿ‘‹

I'm Lorenzo, an NLP Engineer with a strong foundation in Computer Science and Engineering. Currently, I am a dedicated 2-year MSc student in Artificial Intelligence at the University of Bologna, striving to delve deeper into the realm of AI and NLP. Alongside my academic pursuits, Iโ€™ve actively engaged in practical NLP research. Iโ€™m passionate about leveraging the power of AI and NLP to drive innovation and solve complex challenges.

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Unveiling My Journey

Dedicated advocate of deliberate practice, I channel my fervor for the world of AI into continuous skill enhancement. My journey unfolds through Python-powered projects, while also harnessing the capabilities of:

  • NumPy & SciPy for scientific computations
  • Pandas and parallel optimizations like Dask
  • ML/DL solutions with Sklearn and PyTorch (sometimes Lightning โšก๏ธ)
  • NLP using HuggingFace ๐Ÿค—, LangChain, LlamaIndex and BERTopic
  • Docker (Compose if needed) & Kubernetes for orchestrating services
  • Proficient in AWS tools, including SageMaker, S3, Athena, ECS, EKS
  • Pgmpy for probabilistic modeling through Bayesian Networks
  • PROLOG for logic programming
  • MERN stack for web development
  • Linux/Bash & SQL
  • $LaTeX$ for polished essays

Let's Connect ๐Ÿ“ฌ

Feel free to get in touch if you have any questions or feedback. I'm always open to connecting and chatting! ๐Ÿ’ฌ

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Curious to check out my resume? Feel free to take a look!

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