| ChakriCherukuri/mlviz |
97 |
|
0 |
0 |
about 4 years ago |
0 |
|
2 |
mit |
Jupyter Notebook |
| Visualizations of machine learning models and algorithms |
| bhargavvader/pycobra |
84 |
|
0 |
0 |
almost 6 years ago |
7 |
April 16, 2020 |
3 |
mit |
Python |
| python library implementing ensemble methods for regression, classification and visualisation tools including Voronoi tesselations. |
| ptyadana/Data-Science-and-Machine-Learning-Projects-Dojo |
67 |
|
0 |
0 |
about 3 years ago |
0 |
|
0 |
mit |
Jupyter Notebook |
| collections of data science, machine learning and data visualization projects with pandas, sklearn, matplotlib, tensorflow2, Keras, various ML algorithms like random forest classifier, boosting, etc |
| mr-easy/GMM-EM-Python |
41 |
|
0 |
0 |
almost 3 years ago |
0 |
|
0 |
|
Jupyter Notebook |
| Python implementation of EM algorithm for GMM. And visualization for 2D case. |
| davpinto/ml-simulations |
28 |
|
0 |
0 |
over 9 years ago |
0 |
|
0 |
|
R |
| Animated Visualizations of Popular Machine Learning Algorithms |
| biolab/orange3-educational |
25 |
|
1 |
0 |
about 2 years ago |
23 |
October 02, 2023 |
4 |
other |
Python |
| 🍊 🎓 Educational widgets for machine learning and data mining in Orange 3. |
| sagnibak/nac-loss-vis |
6 |
|
0 |
0 |
over 7 years ago |
0 |
|
0 |
mit |
Jupyter Notebook |
| Visualizing loss functions to better understand why Neural Accumulators/Arithmetic Logic Units perform better at certain tasks compared to vanilla MLPs. |
| zainsiddiqui/Predicting-Survival-on-Titanic-with-Machine-Learning-and-Graphical-User-Interface |
6 |
|
0 |
0 |
almost 7 years ago |
0 |
|
0 |
|
Python |
| This program consists of clean and polished Graphical User Interface (GUI) that interacts with 8 Machine Learning models and data visualization tools through the use of different Python libraries. The user can interact with the GUI through selecting which model to run on the testing data on, which then takes them to a screen displaying the prediction results of the testing data as well as the general model accuracy. The screen also includes various buttons that, when selected, display complex and attractive data visualizations on the testing data. |