The aim of this fork is to improve original starter project code for students taking Intro to Machine Learning on Udacity with python 3.8, conda managing and jupyter notebooks.

• Lesson 2: Naive Bayes
• Lesson 3: SVM
• Lesson 4: Decision Trees
• Lesson 5: Choose Your own Algorithm
• Lesson 6: Datasets and Questions
• Lesson 7: Regressions
• Lesson 8: Outliers
• Lesson 9: Clustering
• Lesson 10: Feature Scaling
• Lesson 11: Text Learning
• Lesson 12: Feature Selection
• Lesson 13: PCA
• Lesson 14: Validation
• Lesson 15: Evaluation Metrics
• Lesson 17: Final Project

In this repo newer version of scikit-learn is used. Thus, to get the results expected by the course grader you need to use SVC with gamma='auto', since the default value of gamma changed, see sklearn.svm.SVC docs:

Changed in version 0.22: The default value of gamma changed from 'auto' to 'scale'.

For example:

clf = SVC(kernel='linear', gamma='auto')

To get the correct (acceptable by grader) results set sort_keys='../utils/python2_lesson06_keys.pkl' for feature_format function:

...
data = feature_format(dictionary, features_list, remove_any_zeroes=True, sort_keys='../utils/python2_lesson06_keys.pkl')
...

[...] This will open up a file in the tools folder with the Python 2 key order.

See this for detailed explanation.

$ git clone https://github.com/trsvchn/ud120-projects-py3-jupyter.git
$ cd ud120-projects-v2

link

$ conda env create -f environment.yml

$ conda activate ud120

$ python ./utils/starter.py