| hschen0712/machine-learning-notes |
130 |
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0 |
0 |
about 8 years ago |
0 |
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0 |
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Jupyter Notebook |
| 机器学习笔记 |
| LeBron-Jian/MachineLearningNote |
114 |
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0 |
0 |
over 5 years ago |
0 |
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0 |
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Jupyter Notebook |
| TatevKaren/data-science-popular-algorithms |
101 |
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0 |
0 |
over 2 years ago |
0 |
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0 |
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Jupyter Notebook |
| Data Science algorithms and topics that you must know. (Newly Designed) Recommender Systems, Decision Trees, K-Means, LDA, RFM-Segmentation, XGBoost in Python, R, and Scala. |
| AlanConstantine/MachineLearningNote |
37 |
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0 |
0 |
about 3 years ago |
0 |
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0 |
mit |
Jupyter Notebook |
| 用python实现机器学习各种经典算法 |
| Nikronic/Machine-Learning-Models |
26 |
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0 |
0 |
over 4 years ago |
0 |
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2 |
mit |
Python |
| In This repository I made some simple to complex methods in machine learning. Here I try to build template style code. |
| cconsta1/SexEst |
11 |
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0 |
0 |
about 1 month ago |
0 |
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0 |
apache-2.0 |
Python |
| SexEst is an open-source Streamlit web application for predicting biological sex from skeletal measurements using machine learning (XGBoost, LightGBM, Linear Discriminant Analysis). The best-performing models achieved cross-validated accuracies of ~80–90% on the Goldman (postcranial) and Howells (cranial) datasets. |
