Understanding Machine Learning
The IEEE Egypt AP-S/MTT-S Joint Chapter, Egypt, organizes free workshop series with the collaboration of the AL Ryada University for Science and Technology, RST.
Your outcomes and benefits are the following, but not limited to only that.
* Grasp core machine learning concepts.
* Understand the machine learning workflow.
* Code basic machine learning models.
* Interpret and evaluate model performance.
* Identify and address common machine learning challenges.
* Recognize the limitations of machine learning.
Date and Time
Location
Hosts
Registration
- Start time: 01 Jul 2024 10:00 AM
- End time: 26 Aug 2024 02:00 PM
- All times are (UTC+03:00) Cairo
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Speakers
Eng. Ahmed A. Gomaa of Faculty of Computers and Artificial Intelligence, ALRyada University for Science and Technology
Understanding Machine Learning
Agenda
1. Supervised Learning:
a. Regression: Used for predicting a continuous output variable. Examples:
(1) Linear Regression.
(2) Polynomial Regression.
b. Support Vector Regression (SVR):
c. Classification: Used for predicting a categorical output variable. Examples:
(1) Logistic Regression.
(2) Decision Trees.
(3) Support Vector Machines (SVMs).
(4) Native Bayes.
(5) K-Nearest Neighbors (KNN).
2. Unsupervised Learning:
a. Clustering: grouping data points into clusters based on similarity. Examples:
(1) K-Means Clustering.
We sincerely invite you to attend this amazing workshop to enhance your career and profession.
Media
| Understanding Machine Learning | The IEEE Egypt AP-S/MTT-S Joint Chapter, Egypt, organizes free workshop series with the collaboration of the AL Ryada University for Science and Technology, RST. | 1.95 MiB |