49
/ 100
Real traction, but rough engineering makes it hard for contributors to trust.
This repository helps you learn Python and Machine Learning from scratch.
A low grade is a to-do list, not a judgment of your code
Most gaps here are documentation, tests, and setup, not the code itself. Closing your top 3 gaps alone would lift this repo to C (77).
See your top fixesTop fixes
Highest-impact changes first, ranked by point weight
- 1Tests18pt
Add automated tests. They prove the code works and give contributors confidence to make changes.
- 2CI/CD14pt
Add a step like `run: npm test`, `run: pytest`, or `run: tox` to your workflow file.
- 3CI/CD14pt
Add `pull_request:` to the workflow `on:` triggers.
- 4CI/CD14pt
Add a lint step to catch style issues automatically.
Working through the fixes? Let every push regrade itself.
The free GitHub App rescans this repo on every push and posts the grade as a commit check, so the score climbs without coming back to rescan by hand.
Scorecard
Every check, grouped by category and sorted worst-first
Documentation
68
No license detected.
→ Add a LICENSE file. Without one, nobody can legally use, copy, or contribute to your code.
Contributing guide is too short for full depth credit (−6 pts). 400+ words earns the full +12 pts.
→ Add setup instructions, code style notes, and how to run tests.
README is present.
README documents how to install the project.
Engineering
20
No tests detected anywhere in the repository.
→ Add automated tests. They prove the code works and give contributors confidence to make changes.
No linter or formatter config found.
→ Add a linter config such as .eslintrc.json, .prettierrc, ruff.toml, or .golangci.yml to enforce consistent code style.
No issue or PR templates found (−100 pts).
→ Add .github/ISSUE_TEMPLATE/ with bug_report.md and feature_request.md to guide contributors. It dramatically improves issue quality.
CI is configured (.github/workflows/static.yml).
Lockfile present (Machine Learning/requirements.txt). Installs are reproducible.
Project health
91
No .gitignore found (−60 pts).
→ Add a .gitignore to keep build output, node_modules, and secrets out of version control.
Dependency manifest found (Machine Learning/requirements.txt).
Repository has a description.
Actively maintained (pushed within the last month).
Repository health signals
Activity, community, and responsiveness at scan time
Activity
- 25 / 90Commits (30d / 90d)
- 919Forks
- 5Releaseslatest 5mo ago
Community
- 57% - FairCommunity health
- 1 bus factorlowauthor own >50% of commits
- 2,177Watchers
Responsiveness
- 42d 7hMedian issue response
- 16dMedian PR merge time
- 9Open issues
Repository files73 root entries
- .githubGood: CI is configured (.github/workflows/static.yml).
- assets
- Data Analysis
- Data Scraping from the Web
- Data_Science
- Exploratory Data Analysis
- Google Translate API
- Img
- LinkedIn
- Machine LearningGood: Lockfile present (Machine Learning/requirements.txt). Installs are reproducible.Good: Dependency manifest found (Machine Learning/requirements.txt).
- Machine Learning Advanced Topics
- Machine Learning Interview Prep Questions
- Numpy
- Oil Refineries
- Pandas
- Python
- Release Notes
- .gitpod.Dockerfile
- .gitpod.yml
- Building_Your_First_Machine_Learning_Model.ipynb
- Cheat_sheet_for_Google_Colab.ipynb
- CODE_OF_CONDUCT.mdGood: Code of conduct present.
- Composition_Over_Inheritance.ipynb
- content.html
- CONTRIBUTING.mdIssue: Contributing guide is too short for full depth credit (−6 pts). 400+ words earns the full +12 pts.Fix: Add setup instructions, code style notes, and how to run tests.Issue: Contributing guide lacks a setup section (−12 pts).Fix: Show new contributors how to get a local dev environment running.Issue: Contributing guide lacks a code style section (−8 pts).Fix: Describe your linting/formatting rules and how to run them.Issue: Contributing guide lacks a testing section (−8 pts).Fix: Show contributors how to run the test suite (e.g. npm test, pytest, cargo test).Good: Contributing guide describes the PR/review workflow.Issue: Contributing guide has no code examples (−5 pts).Fix: Add code blocks showing example commands for setup, running tests, and submitting a PR.
- data_load.md
- Demystifying_Feature_Engineering.ipynb
- Dependency_Inversion_Principle_in_Python.ipynb
- Hidden_Layers_of_Understanding_CNN.ipynb
- Hidden_Markov_Models_in_Python.ipynb
- How_to_Efficiently_Compute_Euclidean_Distance_in_Python_Using_NumPy.ipynb
- How_to_get_started_coding_in_Python.ipynb
- How_to_Handle_Missing_Data_in_Pandas_Like_a_Pro.ipynb
- How_to_Structure_Machine_Learning_Projects_with_Clean_Code_Principles_in_Python.ipynb
- index.html
- Interface_Segregation_Principle.ipynb
- Law_of_Demeter.ipynb
- Learning_One_Hot_Encoding_in_Python_the_Easy_Way.ipynb
- Liskov_Substitution_Principle_in_Python.ipynb
- Manipulating_the_data_with_Pandas_using_Python.ipynb
- Mastering_the_Bar_Plot_in_Python.ipynb
- Normalization_vs_Standardization.ipynb
- Open_Closed_Principle_in_Python.ipynb
- Optimizing_Python_Code_with_List_Comprehensions.ipynb
- Pick_up_Line_Generator.ipynb
- Playing_with_Titanic_Dataset.ipynb
- Predicting_Loan_Default_Using_Decision_Trees.ipynb
- Predicting_PewDiePie's_daily_subscribers_using_Machine_Learning_.ipynb
- Presenting_Python_code_using_RISE.ipynb
- Range_built_in_function.ipynb
- Reading_An_Image_In_Python_(Without_Using_Special_Libraries).ipynb
- README.mdGood: README is present.Good: README is well structured with multiple sections.Good: README includes screenshots or visuals. Great for first impressions.Issue: README has no code examples (−15 pts).Fix: Show a quick-start snippet so contributors can see what using your project looks like.Good: README links to a live demo or deployed app.Good: README includes status badges.Good: README documents how to install the project.Good: README documents how to run the project.
- releases.html
- Rendering_Images_inside_a_Pandas_DataFrame.ipynb
- Rule_Based_System_with_Python.ipynb
- Single_Responsibility_Principle.ipynb
- Smart_Resume_Ranker_with_Python.ipynb
- Speech_Recognition_using_Python.ipynb
- Splitting_the_dataset_into_three_sets.ipynb
- String_Concatenation_Exercise_Answers.ipynb
- String_Concatenation_Exercise_Questions.ipynb
- Telling_Stories_With_Data.md
- The_two_Google_Search_Python_Libraries_you_should_never_miss.ipynb
- Time_Series_Forecasting_with_Pandas.ipynb
- Top_Python_Libraries_Used_In_Data Science.ipynb
- Transit_Data_Calgary_2025.ipynb
- Understanding_Virtual_Environments_in_Python.ipynb
- University_of_Regina_Professor's_salary.ipynb
- Unlocking_Time_Series_Forecasting_with_Facebook_Prophet.ipynb
- update_readme.py
- Using_the_Pandas_Data_Frame_as_a_Database_.ipynb
- Using_the_Pandas_DataFrame_in_Day_To_Day_Life.ipynb
- Wikipedia_API_for_Python.ipynb
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