kabirnagpal / 15DaysofML

This repository is a smaller version of 100DaysofML to motivate beginners to take up that challenge and dive deeper into the domain of Machine Learning.

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15DaysofML

This repository is a smaller version of 100DaysofML to motivate beginners to take up that challenge and dive deeper into the domain of Machine Learning.

  1. Worked with StratifiedKFold and XGBoost for a private anomaly detection dataset. F1 - Score was found to be around 96%.
  2. Worked on Data Visualisations using Pairplot and Distplot to test Hypothesis and measure Skewness. Also worked on increasing Correalation of X with Y.
  3. Worked on Feature extractions for decreasing time consumed to train the model. Models used
  4. Worked with XGBoost on the dataset and finetuned to reach an F1-score of 96.2% on an anomalies detection dataset.
  5. Worked on reducing skewness of the dataset. Also worked with Power Tranform and understood the working.
    • Right skewed: log transform
    • Left skewed : square transform
  6. Learned EDA technique and and new types of graphs in Sea Born like swarmplot, KDE etc.
  7. Half way through writing research paper, learned about ResNet in depth, learned BoxCox for reducing skewness.
  8. Tried a skewness reduction method on Pet Adoption data. Learned more about hypothesis and P-value.
  9. After multiple tests on Training set, I applied the mehtods to test datatset. Sadly the accuracy achieved was only 88%. Worked more on hypothesis understanding.
  10. Researched about autocorrect methods using Deep Learning and distance method.
  11. Trying to implement Bi Directional LSTM
  12. Back to basics for Multilayer perceptron from scratch. Associative Network trial in Matlab
  13. Recieved Assignment related to geospatial data for internship. Data Analysis + Classification
  14. Read and understood these research paper
  15. Read a number of blogs:

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This repository is a smaller version of 100DaysofML to motivate beginners to take up that challenge and dive deeper into the domain of Machine Learning.