Building Intelligent Model

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Building Intelligent Model

Dear Colleagues,
Dear IEEE Students,

You are kindly invited to the full day AI/ML training entitled "Building Intelligent Model" with two trainer experts in this area. 

Please register ASAP https://forms.gle/P7ffeU6DaYjdcoKDA to save your seat because the seats are limited.

This big event aims to unite students from various universities for a full day of training about AI and Machine Learning with real applications.

This training day can provide participants with a comprehensive understanding of the foundational concepts and practical techniques in AI and machine learning. · 

At the end of the event, attendees should be able to:

o   Prepare and process data effectively for AI & machine learning tasks.

o   Understand and apply various AI & machine learning algorithms.

o   Implement AI & machine learning models using Keras.

o   Address key challenges in AI & machine learning.

o   Explore real-world applications

Regards,
Abdallah Kassem 
(on Behalf of NDU IEEE SB, IEEEE SIGHT-Lebanon, IEEE Computer Lebanon Chapter & IEEE Lebanon JT chapter CAS/PE/PEL/IE)


  Date and Time

  Location

  Hosts

  Registration


  • Date: 07 Dec 2024
  • Time: 06:00 AM UTC to 02:30 PM UTC
  • Add_To_Calendar_icon Add Event to Calendar
  • Notre Dame University
  • Barsa
  • Koura, Lebanon
  • Lebanon 0000
  • Building: Conference Room
  • Click here for Map
  • Contact Event Hosts




Agenda

8:00-8:45: Registration & refreshment

8:45-9:00: Opening Ceremony

9:00-12:00: Session 1: Data Preparation for Machine Learning

1. Introduction to Data Preparation

2. Understanding Different Types of Data

3. Data Collection and Exploration

4. Data Cleaning and Pre-processing

5. Data Transformation Techniques

6. Splitting the Data for Training and Testing

12:00-13:00 Lunch Break

13:00-16:00: Session 2: Introduction to Machine Learning

1. Introduction

2. Supervised Learning (K-NN, SVM, ...)

3. Unsupervised Learning (Kmeans, ...)

4. Practical Examples of Supervised and Unsupervised Learning

5. Key Challenges in Machine Learning

6. Real-world Applications of Supervised and Unsupervised Learning


AI/ML Training Day