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GitHub / cemalaytekin / Fashion-Mnist-With-Keras
Classify the Fashion-MNIST dataset with keras with tensorflow, using a Convolutional Neural Network (CNN) architecture.
JSON API: https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/cemalaytekin%2FFashion-Mnist-With-Keras
Stars: 1
Forks: 0
Open Issues: 15
License: None
Language: Jupyter Notebook
Repo Size: 17.9 MB
Dependencies:
94
Created: over 4 years ago
Updated: almost 3 years ago
Last pushed: over 1 year ago
Last synced: about 1 year ago
Files
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Readme
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Dependencies
requirements.txt
pypi
- Jinja2 ==2.10.1
- Keras ==2.2.4
- Keras-Applications ==1.0.7
- Keras-Preprocessing ==1.0.9
- Markdown ==3.1
- MarkupSafe ==1.1.1
- PyYAML ==5.1
- Pygments ==2.3.1
- Send2Trash ==1.5.0
- Werkzeug ==0.15.2
- absl-py ==0.7.1
- appnope ==0.1.0
- astetik ==1.9.8
- astor ==0.7.1
- attrs ==19.1.0
- backcall ==0.1.0
- bleach ==3.1.0
- certifi ==2019.3.9
- chances ==0.1.6
- chardet ==3.0.4
- cycler ==0.10.0
- decorator ==4.4.0
- defusedxml ==0.6.0
- entrypoints ==0.3
- gast ==0.2.2
- geonamescache ==1.0.2
- grpcio ==1.20.1
- h5py ==2.9.0
- idna ==2.8
- ipykernel ==5.1.0
- ipython ==7.5.0
- ipython-genutils ==0.2.0
- ipywidgets ==7.4.2
- jedi ==0.13.3
- jsonschema ==3.0.1
- jupyter ==1.0.0
- jupyter-client ==5.2.4
- jupyter-console ==6.0.0
- jupyter-core ==4.4.0
- kerasplotlib ==0.1.4
- kiwisolver ==1.1.0
- matplotlib ==2.2.3
- mistune ==0.8.4
- mock ==3.0.3
- nbconvert ==5.5.0
- nbformat ==4.4.0
- notebook ==5.7.8
- numpy ==1.16.3
- pandas ==0.24.2
- pandocfilters ==1.4.2
- parso ==0.4.0
- patsy ==0.5.1
- pexpect ==4.7.0
- pickleshare ==0.7.5
- plotly ==3.8.1
- prometheus-client ==0.6.0
- prompt-toolkit ==2.0.9
- protobuf ==3.7.1
- psutil ==5.6.2
- ptyprocess ==0.6.0
- pycosat ==0.6.3
- pydot ==1.4.1
- pyparsing ==2.4.0
- pyrsistent ==0.15.1
- python-dateutil ==2.8.0
- python-slugify ==3.0.2
- pytz ==2019.1
- pyzmq ==18.0.1
- qtconsole ==4.4.4
- requests ==2.21.0
- retrying ==1.3.3
- ruamel.yaml ==0.15.94
- scikit-learn ==0.20.3
- scipy ==1.2.1
- seaborn ==0.9.0
- six ==1.12.0
- sklearn ==0.0
- statsmodels ==0.9.0
- tensorboard ==1.13.1
- tensorflow ==1.13.1
- tensorflow-estimator ==1.13.0
- termcolor ==1.1.0
- terminado ==0.8.2
- testpath ==0.4.2
- text-unidecode ==1.2
- tornado ==6.0.2
- tqdm ==4.31.1
- traitlets ==4.3.2
- urllib3 ==1.24.3
- wcwidth ==0.1.7
- webencodings ==0.5.1
- widgetsnbextension ==3.4.2
- wrangle ==0.6.2
Dockerfile
docker
- gaarv/jupyter-keras latest build