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https://github.com/1ayanabil1/machine-learning-using-python-by-ibm
https://github.com/1ayanabil1/machine-learning-using-python-by-ibm
course course-project coursera coursework ibm ibm-cloud ibm-watson ibmcode machine-learning machine-learning-algorithms machinelearning python python-script python3
Last synced: 1 day ago
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- Host: GitHub
- URL: https://github.com/1ayanabil1/machine-learning-using-python-by-ibm
- Owner: 1AyaNabil1
- Created: 2023-10-09T12:59:12.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2023-10-09T13:20:34.000Z (about 1 year ago)
- Last Synced: 2024-11-10T11:40:00.640Z (about 2 months ago)
- Topics: course, course-project, coursera, coursework, ibm, ibm-cloud, ibm-watson, ibmcode, machine-learning, machine-learning-algorithms, machinelearning, python, python-script, python3
- Language: Jupyter Notebook
- Homepage:
- Size: 542 KB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# 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](https://github.com/1AyaNabil1/Machine-Learning-using-Python-by-IBM/blob/main/%5B1%5D%20Simple%20Linear%20Regression%20(CO2).ipynb).
2. [Multiple Linear Regression](https://github.com/1AyaNabil1/Machine-Learning-using-Python-by-IBM/blob/main/%5B2%5D%20Mulitple%20Linear%20Regression%20(CO2).ipynb).
3. [Polynomial Regression](https://github.com/1AyaNabil1/Machine-Learning-using-Python-by-IBM/blob/main/%5B3%5D%20Polynomial%20Regression%20(CO2).ipynb).
4. [Non-linear Regression](https://github.com/1AyaNabil1/Machine-Learning-using-Python-by-IBM/blob/main/%5B4%5D%20None%20Linear%20Regression%20(China).ipynb).
5. [K-Nearest Neighbors](https://github.com/1AyaNabil1/Machine-Learning-using-Python-by-IBM/blob/main/%5B5%5D%20K%20Nearest%20neighbors%20(CustCat).ipynb).
6. [Decision Trees](https://github.com/1AyaNabil1/Machine-Learning-using-Python-by-IBM/blob/main/%5B6%5D%20Decision%20Trees%20(Drug).ipynb).
7. [Logistic Regression](https://github.com/1AyaNabil1/Machine-Learning-using-Python-by-IBM/blob/main/%5B7%5D%20Logistic%20Regression%20(Churn).ipynb).
8. [Suport Vector Machine - Cancer detection](https://github.com/1AyaNabil1/Machine-Learning-using-Python-by-IBM/blob/main/%5B8%5D%20SVM%20(cancer).ipynb).
9. [K-Means - Customer Segmentation](https://github.com/1AyaNabil1/Machine-Learning-using-Python-by-IBM/blob/main/%5B9%5D%20K-Means%20(Customer%20Seg).ipynb).
10. [Hierarchical Clustering - Cars clustering](https://github.com/1AyaNabil1/Machine-Learning-using-Python-by-IBM/blob/main/%5B12%5D%20RecSys%20(Collaborative%20Filtering%20movies).ipynb).
11. [DBSCAN - Weather Station Clustering](https://github.com/1AyaNabil1/Machine-Learning-using-Python-by-IBM/blob/main/%5B11%5D%20DBSCN%20(weather).ipynb).
12. [Colaborative Filtering - Creation of a recommendation system](https://github.com/1AyaNabil1/Machine-Learning-using-Python-by-IBM/blob/main/%5B12%5D%20RecSys%20(Collaborative%20Filtering%20movies).ipynb).
13. [Content Based Filtering - Creation of a recommendation system](https://github.com/1AyaNabil1/Machine-Learning-using-Python-by-IBM/blob/main/%5B13%5D%20RecSys%20(Content%20Based%20movies).ipynb).
14. [Final project](https://github.com/1AyaNabil1/Machine-Learning-using-Python-by-IBM/blob/main/Final%20Assignment.ipynb) with full pipeline and aplication of classification algorithms: KNN, Decision Treens, SVM and Logistic Regression .
## This Course Certificate:
#### ***Acknowledgment!!!***
Warm Regards, \
Aya Nabil \
Email: [email protected]