https://github.com/smirnovlad/data-science-notebooks

A collection of various data analysis approaches
https://github.com/smirnovlad/data-science-notebooks

data-science deep-learning kaggle machine-learning numpy pandas pytorch

Last synced: 15 days ago
JSON representation

A collection of various data analysis approaches

• Host: GitHub
• URL: https://github.com/smirnovlad/data-science-notebooks
• Owner: smirnovlad
• Created: 2023-11-17T07:31:43.000Z (12 months ago)
• Default Branch: main
• Last Pushed: 2024-06-01T11:22:38.000Z (6 months ago)
• Last Synced: 2024-10-09T04:22:50.053Z (about 1 month ago)
• Topics: data-science, deep-learning, kaggle, machine-learning, numpy, pandas, pytorch
• Language: Jupyter Notebook
• Homepage:
• Size: 11.9 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

Awesome Lists containing this project

README

        
# Data science notebooks

This repository comprises a compilation of my solutions and experiments in machine learning problems. Jupyter notebooks encompass research on open-source datasets and solutions to Kaggle competitions. Here, you can explore a diverse range of approaches and techniques for data analysis, along with the application of machine and deep learning methods.

## Kaggle

- [Simpsons classification](https://www.kaggle.com/competitions/journey-springfield), [simpsons.ipynb](kaggle/simpsons.ipynb) (DLS assignment)

## MIPT ML courses

### Generic

- [Wine dataset](https://scikit-learn.org/stable/modules/generated/sklearn.datasets.load_wine.html), [wine.ipynb](mipt_ml_courses/generic/wine.ipynb)

- [Regression task with a raw dataset](https://www.kaggle.com/competitions/fall-ml2-mipt-2023/overview), [raw_dataset_regression.ipynb](mipt_ml_courses/generic/raw_dataset_regression.ipynb)

### Computer vision

- [Breast cancer cells segmentation](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10490494/), [cancer_cells_segmentation](mipt_ml_courses/cv/cancer_cells_segmentation.ipynb)

TODO: add classification metrics such as Precision, Recall, etc.

- [Panorama stitching](mipt_ml_courses/cv/panorama_stitching.ipynb)

### Advanced

[Repository](https://github.com/andriygav/MachineLearningSeminars)

- [Analysis of CNN on the EMNIST-letters dataset](mipt_ml_courses/advanced/cnn_emnist.ipynb)

- [Prediction of POS tags for tokens in the NERUS dataset using LSTM](mipt_ml_courses/advanced/lstm_nerus.ipynb)

- [Analysis of an autoencoder in the sentence reconstruction task for the Twitter dataset](mipt_ml_courses/advanced/autoencoder_twitter.ipynb)

- [Generation of image annotations for the COCO dataset](mipt_ml_courses/advanced/image_captioning_coco.ipynb)

## Deep Learning School

- [PH2 Dataset images](https://www.fc.up.pt/addi/ph2%20database.html), [ph2_semantic_segmentation.ipynb](dls/ph2_semantic_segmentation.ipynb)