/Machine-Learning-using-Python-by-IBM

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Machine Learning with Python IBM

This course dives into the basics of machine learning using an approachable, and well-known programming language, Python.

In this course, I did reviewed two main components:

  • First, I learned about the purpose of Machine Learning and where it applies to the real world.
  • Second, I got a general overview of Machine Learning topics such as supervised vs unsupervised learning, model evaluation and Machine Learning algorithms.

In this course, it was possible to practice with real-life examples of Machine learning and see how it affects society in ways I may not have guessed!

By just putting in a few hours a week, this is what i got.

  1. Review some skills such as regression, classification, clustering, sci-kit learn and SciPy
  2. New projects, including cancer detection, predicting economic trends, predicting customer churn, recommendation engines, and many more.
  3. And a certificate in machine learning.

Skills covered and its notebooks:

  1. Simple Linear Regression.
  2. Multiple Linear Regression.
  3. Polynomial Regression.
  4. Non-linear Regression.
  5. K-Nearest Neighbors.
  6. Decision Trees.
  7. Logistic Regression.
  8. Suport Vector Machine - Cancer detection.
  9. K-Means - Customer Segmentation.
  10. Hierarchical Clustering - Cars clustering.
  11. DBSCAN - Weather Station Clustering.
  12. Colaborative Filtering - Creation of a recommendation system.
  13. Content Based Filtering - Creation of a recommendation system.
  14. Final project with full pipeline and aplication of classification algorithms: KNN, Decision Treens, SVM and Logistic Regression .

This Course Certificate:

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Acknowledgment!!!

Warm Regards,
Aya Nabil
Email: ayanabil3200@gmail.com