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missingno

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In this project, we created an 'expected goals' metric to help us assess a team's performance rather than the actual number of goals scored. We merged this metric with the calculation of a team's offensive and defensive ratings, which are updated after every game, to create a classification model that predicts the outcome of future matches, as w…

  • Updated Jun 17, 2021
  • Python

EDA for more than 30K game ratings collected from [IGDB API](https://api-docs.igdb.com/#about) using [igdb-api-v4 for python](https://github.com/twitchtv/igdb-api-python). This notebook explores any common trends for games that have ratings from igdb and external critics.

  • Updated Nov 8, 2022
  • Jupyter Notebook

A classification approach to the machine learning Titanic survival challenge on Kaggle.Data visualisation, data preprocessing and different algorithms are tested and explained in form of Jupyter Notebooks

  • Updated Jun 15, 2023
  • Jupyter Notebook

Exploring 118 wells of 1 MM+ rows and 29 columns of wireline petrophysical data using the Pandas library. Analysed & Visualised wireline logs petrophysical dataset using - Pandas, Numpy, Matplotlib, Plotly & seaborn libraries Discovered insights of wireline logs quality & interpretation (missing data and imbalance class

  • Updated Nov 20, 2023
  • Jupyter Notebook

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