Machine Learning Essentials: Model Training & Optimization

#WorkshopSeriesIntroduction #DataModelingWorkshop #ArtificialIntelligence #MachineLearning #IEEEModelthon1_0 #KagglePreparation #DataScienceTraining #ModelOptimization #ScikitLearn #MLAlgorithms #EnsembleModeling #AIWorkshop #DataDrivenInsights #ModelTuning #MLPerformance

Workshop Series Introduction

This workshop is one of a series of workshops that aim to enhance understanding of data modeling processes for those interested in artificial intelligence and machine learning. Specifically, it is designed to prepare participants for the first edition of the upcoming IEEEModelthon 1.0 on Kaggle.

Workshop Overview

In this workshop, you will explore various data modeling tasks and learn about different types of machine learning algorithms. In addition, you will be introduced to key data modeling concepts and the most common challenges encountered in the learning process and how to fine-tune your model's performance.

Purpose

Primarily, this workshop covers methods for training machine learning models using the sklearn library, based on the pre-prepared data from the previous step, and how to check their performance and adjust their parameters, if needed, using one of the optimization algorithms!

Objective and Outcome

This workshop is essential for anyone in a data-driven field. Mainly, the outcome of this phase is a list of 3 to 5 promising models and integrating them in one amazing ensemble model!


For more information about the IEEEModelthon1.0, click here.

Go to IEEEModelthon1.0