العربية
- Duration: 16 hours
Categories: Information & Communication Technology (ICT)
| This course covers the essentials for Machine Learning using Python libraries, including advanced components such as feature engineering, attribute combination, transformers, and empirical visualizations. Learn how real machine learning algorithms work, from preprocessing to feature scaling, from training and tuning to visualization of the models; how to save and load machine learning algorithms, how to build the models using various libraries; and how to work with the models and the plots. |
After completing this course you will be able to:
- Open, query and gain insights on datasets.
- Prepare the data for Machine Learning algorithms.
- Train and test machine learning algorithms.
- Adjust and publish Python solutions.
- Launch, monitor, and maintain your machine learning project.
- Install and Configure Anaconda and Jupyter Notebook Workspace.
- Prepare the Jupyter Workspace.
- Discover and visualize the data to gain insights.
- Conduct Attribute Correlations and Combinations.
- Handle Text and Categorical Attributes using scikitlearn.
- Apply Feature Scaling.
- Train and Evaluate the Training Set.
- Perform Cross Validation and Various Search Methods.
- Evaluate Your System on the Test Set.
- Launch, monitor, and maintain your machine learning system.
Students and Employees in Organizations
17-20/02/2025
English – Python – Jupyter Notebook
Sohar University
Omar said Al Shibli
Phone Number: 91271393 – 26850111
Email: OSShibli@su.edu.om
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