Titanic Classification
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
| Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
|---|---|---|---|---|---|---|---|---|---|---|
| Orange3 | 4,469 |  | 57 | 47 | 3 months ago | 63 | October 31, 2023 | 99 | other | Python |
| 🍊 :bar_chart: :bulb: Orange: Interactive data analysis | ||||||||||
| Datascience_artificialintelligence_utils | 369 | 9 months ago | 6 | Jupyter Notebook | ||||||
| Examples of Data Science projects and Artificial Intelligence use-cases | ||||||||||
| Data Science Toolkit | 185 | 2 years ago | 1 | HTML | ||||||
| Collection of stats, modeling, and data science tools in Python and R. | ||||||||||
| Satellite_imagery_analysis | 123 | 2 years ago | 2 | gpl-3.0 | Jupyter Notebook | |||||
| Implementation of Machine Learning and Deep Learning techniques to find insights from the satellite data. | ||||||||||
| Aiml Projects | 44 | 3 years ago | mit | Jupyter Notebook | ||||||
| Projects I completed as a part of Great Learning's PGP - Artificial Intelligence and Machine Learning | ||||||||||
| Predictive Analytics For Business Nanodegree | 43 | 5 years ago | Jupyter Notebook | |||||||
| Kai Sheng Teh - Udacity Predictive Analytics for Business Nanodegree | ||||||||||
| Facerec Bias Bfw | 40 | 2 years ago | 9 | bsd-3-clause | Jupyter Notebook | |||||
| Source code and notebooks to reproduce experiments and benchmarks on Bias Faces in the Wild (BFW). | ||||||||||
| Deep_learning_projects | 28 | 3 years ago | 2 | Jupyter Notebook | ||||||
| Stock Market Analysis | 27 | 8 months ago | Jupyter Notebook | |||||||
| Exploratory analysis, visualization of stock market data along with predictions made on it using different techniques. | ||||||||||
| Secom Detecting Defected Items | 24 | 5 years ago | gpl-3.0 | Jupyter Notebook | ||||||
| Anamoly Detection for Detecting Defected Manufactured Semi-Conductors, as in this case of Classification, the Defected Chips would be very less in comparison to perfect Chips so we have apply either Over-Sampling or Under-Sampling. | ||||||||||
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Python
Jupyter Notebook
Machine Learning
Dataset
Classification
Data Visualization
Kaggle