data-science-ipython-notebooks abieth · COMPLETED
Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.
github.com/abieth/data-science-ipython-notebooks · ★ 1 · Forks 0 · Size 47.9 MB
SUMMARY
Technologies 9
Scored 9
Observed 9
Practices 6
Evidence 9
Skips 0
COVERAGE
Analyzed 261 files · 543 commits · 0 API calls
TECHNOLOGIES & DEPTH
Dockerfile LANGUAGE Depth 70
1 files · PRODUCTION
Markdown LANGUAGE Depth 70
5 files · PRODUCTION
YAML LANGUAGE Depth 70
2 files · PRODUCTION
Python LANGUAGE Depth 70
57 files · PRODUCTION
NumPy LIBRARY Depth 85
29 files · PRODUCTION
RabbitMQ MESSAGE_BROKER Depth 88
5 files · CONFIGURATION
Redis CACHE Depth 65
1 files · CONFIGURATION
TypeScript LANGUAGE Depth 78
5 files · PRODUCTION
pandas LIBRARY Depth 70
3 files · PRODUCTION
PRACTICES
documentation · observedautomated_tests · observedcontinuous_integration · absentcontainerization · observedlinting · absentformatting · absent
ACTIVITY & OWNERSHIP
First commit 2015-01-23
Last commit 2019-02-11
Active months 30
Commits 543