Advanced Hyperparameter Tuning and Model Selection Course

Enhance your machine learning skills with this course, focusing on advanced techniques in hyperparameter tuning and model selection for optimal performance.

Artificial Intelligence and Machine Learning Courses Confirmed

Training Locations

This Advanced Hyperparameter Tuning and Model Selection Course is available in multiple cities. Please select your preferred location from the list below

Durrës

Albania

Tirana

Albania

Andorra la Vella

Andorra

Escaldes-Engordany

Andorra

Innsbruck

Austria

Salzburg

Austria

Vienna

Austria

Gomel

Belarus

Minsk

Belarus

Antwerp

Belgium

Brussels

Belgium

Banja Luka

Bosnia and Herzegovina

Sarajevo

Bosnia and Herzegovina

Plovdiv

Bulgaria

Sofia

Bulgaria

Dubrovnik

Croatia

Split

Croatia

Zagreb

Croatia

Limassol

Cyprus

Nicosia

Cyprus

Brno

Czech Republic

Prague

Czech Republic

Aarhus

Denmark

Copenhagen

Denmark

Tallinn

Estonia

Tartu

Estonia

Helsinki

Finland

Tampere

Finland

Lyon

France

Marseille

France

Nice

France

Paris

France

Berlin

Germany

Frankfurt

Germany

Hamburg

Germany

Munich

Germany

Athens

Greece

Thessaloniki

Greece

Budapest

Hungary

Debrecen

Hungary

Akureyri

Iceland

Reykjavík

Iceland

Cork

Ireland

Dublin

Ireland

Florence

Italy

Milan

Italy

Naples

Italy

Rome

Italy

Pristina

Kosovo

Prizren

Kosovo

Liepāja

Latvia

Riga

Latvia

Schaan

Liechtenstein

Vaduz

Liechtenstein

Kaunas

Lithuania

Vilnius

Lithuania

Esch-sur-Alzette

Luxembourg

Luxembourg City

Luxembourg

St. Julian's

Malta

Valletta

Malta

Bălți

Moldova

Chișinău

Moldova

La Condamine

Monaco

Monte Carlo

Monaco

Budva

Montenegro

Podgorica

Montenegro

Amsterdam

Netherlands

Rotterdam

Netherlands

The Hague

Netherlands

Ohrid

North Macedonia

Skopje

North Macedonia

Bergen

Norway

Oslo

Norway

Gdańsk

Poland

Kraków

Poland

Warsaw

Poland

Faro

Portugal

Lisbon

Portugal

Porto

Portugal

Bucharest

Romania

Cluj-Napoca

Romania

City of San Marino

San Marino

Serravalle

San Marino

Belgrade

Serbia

Novi Sad

Serbia

Bratislava

Slovakia

Košice

Slovakia

Bled

Slovenia

Ljubljana

Slovenia

Barcelona

Spain

Madrid

Spain

Valencia

Spain

Gothenburg

Sweden

Stockholm

Sweden

Bern

Switzerland

Geneva

Switzerland

Zurich

Switzerland

Kyiv

Ukraine

Lviv

Ukraine

Odesa

Ukraine

Dubai

United Arab Emirates

Birmingham

United Kingdom

Edinburgh

United Kingdom

London

United Kingdom

Manchester

United Kingdom

Rome (Vatican-adjacent)

Vatican City

Training Outlines

Introduction

In the rapidly evolving field of machine learning, the ability to effectively tune hyperparameters and select models is crucial for achieving optimal performance. This advanced course is designed for professionals who seek to enhance their skills in hyperparameter tuning techniques and model selection strategies. Participants will gain hands-on experience with state-of-the-art tools and methodologies to improve model performance in various applications.

Understand the impact of hyperparameters on model performance.
Explore advanced techniques for hyperparameter tuning.
Delve into model selection methods and criteria.
Implement hyperparameter optimization algorithms.
Evaluate and compare different machine learning models effectively.

Course Outlines

Day 1: Foundations of Hyperparameter Tuning

Introduction to hyperparameters and their significance in machine learning.
Overview of basic tuning methods: Grid Search and Random Search.
Understanding the bias-variance trade-off.
Model evaluation metrics and their importance in tuning.
Hands-on session: Implementing basic tuning techniques in Python.

Day 2: Advanced Hyperparameter Tuning Techniques

Introduction to advanced optimization methods: Bayesian Optimization.
Leveraging Gradient-based optimization for hyperparameter tuning.
Exploration of Genetic Algorithms for tuning complex models.
Use of Hyperopt and Optuna libraries in tuning processes.
Practical session: Implementing advanced techniques in real-world datasets.

Day 3: Model Selection Strategies

Criteria for selecting machine learning models.
Cross-validation techniques and their role in model selection.
Automated model selection using AutoML tools.
Comparative analysis of models using statistical tests.
Lab session: Applying model selection techniques to benchmark datasets.

Day 4: Implementing Hyperparameter Optimization Algorithms

Deep dive into different hyperparameter optimization libraries and frameworks.
Parallelization and distributed hyperparameter tuning.
Case studies: Successful applications of hyperparameter optimization.
Common pitfalls and troubleshooting in parameter tuning.
Scripting a complete tuning pipeline with orchestrated runs.

Day 5: Evaluation and Comparative Analysis

Evaluating model performance post-hyperparameter tuning.
Comparison metrics for multi-model evaluation.
Visualization techniques for hyperparameter tuning results.
Reporting improvements and insights from optimized models.
Capstone project presentation and feedback session.

Training Schedule

Below is the table of cities along with the respective dates for the upcoming training sessions of Advanced Hyperparameter Tuning and Model Selection Course. Please review the schedule to find the most convenient option for you. You can also use the below search bar to type the city name and filter the results.