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emirkmo authored Jan 23, 2024
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![Coverage](https://img.shields.io/endpoint?url=https://gist.githubusercontent.com/emirkmo/092a8fbf51f22d7ccf5fc01059f5d5d4/raw/rawsight_badge.json)
# RawSight ML: Raw Python/Numpy ML Algorithms
### Grants insight into ML algorithms with simple, object-oriented, raw `Python`/`Numpy` implementations tested against `SKLearn`/`Tensorflow`
libraries.

The library is developed based on labs for Stanford ML (Andrew NG's/Deeplearning.ai's) new Machine Learning course on Coursera and the repo includes solutions that use the underlying `rawsight` library developed by me to cover the algorithms from the course.
However,these are implemented in Python following Object-Oriented Design principles, vectorization by default with `numpy`, and clean code practices
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are left to the
actual lab jupyter notebook, which is easier to use, and can be found by enrolling
in the course on Coursera.
The code is written by me to complete the lab, so is not copied. The
The code is written by me to complete the lab, and was not copied. However, full disclosure;
I started using github co-pilot after the midway point of the second course as I
had started a new job and found myself with less time. So the NN code is heavily
AI inspired.

## Design decisions

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Coverage

Coverage Report
FileStmtsMissCoverMissing
rawsight
   __init__.py90100% 
   input_validation.py1444 71%
   normalization.py952121 78%
   optimizers.py411515 63%
   regression.py972121 78%
   scoring.py311 67%
rawsight/cost_functions
   __init__.py20100% 
   cost_function_factory.py5588 85%
   cost_functions.py4077 82%
   regularization.py2333 87%
rawsight/datasets
   __init__.py10100% 
   datasets.py943939 59%
rawsight/models
   __init__.py40100% 
   linear.py2333 87%
   logistic.py2744 85%
   model.py1123434 70%
   polynomial.py1188 27%
   softmax.py341818 47%
rawsight/nn
   __init__.py00100% 
   layers.py575757 0%
   networks.py282828 0%
rawsight/tests
   __init__.py00100% 
   test_binary_tree.py260100% 
   test_linear_regression.py6433 95%
   test_logistic_regression.py5644 93%
   test_normalization.py4555 89%
   test_softmax.py431616 63%
rawsight/trees
   __init__.py40100% 
   _splitter_protocol.py611 83%
   binary_tree.py290100% 
   infogain.py2922 93%
   splitting.py3011 97%
   tree.py50100% 
   tree_builder.py4711 98%
TOTAL115430474% 

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