Online or onsite, instructor-led live AdaBoost training courses demonstrate through interactive hands-on practice how to use AdaBoost to build boosting algorithms for machine learning with Python.
AdaBoost training is available as "online live training" or "onsite live training". Online live training (aka "remote live training") is carried out by way of an interactive, remote desktop. Onsite live AdaBoost training can be carried out locally on customer premises in the US or in NobleProg corporate training centers in the US.
AdaBoost is also known as Adaptive Boosting.
NobleProg -- Your Local Training Provider
Testimonials
Convolution filter
Francesco Ferrara - Inpeco SpA
Course: Introduction to Machine Learning
The knowledge of the trainer was very high and the material was well prepared and organized.
Otilia - Gareth Morgan, TCMT
Course: Machine Learning with Python – 2 Days
I thought the trainer was very knowledgeable and answered questions with confidence to clarify understanding.
Jenna - Gareth Morgan, TCMT
Course: Machine Learning with Python – 2 Days
Working from first principles in a focused way, and moving to applying case studies within the same day
Maggie Webb - Margaret Elizabeth Webb, Department of Jobs, Regions, and Precincts
Course: Artificial Neural Networks, Machine Learning, Deep Thinking
It was very interactive and more relaxed and informal than expected. We covered lots of topics in the time and the trainer was always receptive to talking more in detail or more generally about the topics and how they were related. I feel the training has given me the tools to continue learning as opposed to it being a one off session where learning stops once you've finished which is very important given the scale and complexity of the topic.
Jonathan Blease
Course: Artificial Neural Networks, Machine Learning, Deep Thinking
There were many exercises and interesting topics.
L M ERICSSON LIMITED
Course: Machine Learning
The Jupyter notebook form, in which the training material is available
L M ERICSSON LIMITED
Course: Machine Learning
I liked the lab exercises.
Marcell Lorant - L M ERICSSON LIMITED
Course: Machine Learning
The trainer was so knowledgeable and included areas I was interested in
Mohamed Salama
Course: Data Mining & Machine Learning with R
The enthusiasm to the topic. The examples he made an he explained it very well. Sympatic. A little to detailed for beginners. For managers, it could be more abstract in fewer days. But it was designed to fit and we had a good alignment in advance.
Benedikt Chiandetti - HDI Deutschland Bancassurance Kundenservice GmbH
Course: Machine Learning Concepts for Entrepreneurs and Managers
The explaination
Wei Yang Teo - Ministry of Defence, Singapore
Course: Machine Learning with Python – 4 Days
The trainer took the time to answer all our questions.
Ministry of Defence, Singapore
Course: Machine Learning with Python – 4 Days
The way of transferring knowledge and the knowledge of the trainer.
Jakub Rękas - Sebastian Pawłowski, Bitcomp Sp. z o.o.
Course: Machine Learning on iOS
I like that it focuses more on the how-to of the different text summarization methods
Course: Text Summarization with Python
Working with real industry-leading ML tools, real datasets and being able to consult with a very experienced data scientist.
Zakład Usługowy Hakoman Andrzej Cybulski
Course: Applied AI from Scratch in Python
That it was applying real company data. Trainer had a very good approach by making trainees participate and compete
Jimena Esquivel - Zakład Usługowy Hakoman Andrzej Cybulski
Course: Applied AI from Scratch in Python
The trainer was a professional in the subject field and related theory with application excellently
Fahad Malalla - Tatweer Petroleum
Course: Applied AI from Scratch in Python
Bardzo merytoryczne szkolenie, bardzo duża wiedza prowadzącego.
Danuta Haber, Orange Szkolenia Sp. z o.o.
Course: Feature Engineering for Machine Learning
Humor prowadzącego.
Danuta Haber, Orange Szkolenia Sp. z o.o.
Course: Feature Engineering for Machine Learning
Wiedza i umiejetnosc jej przekazania
Danuta Haber, Orange Szkolenia Sp. z o.o.
Course: Feature Engineering for Machine Learning
I enjoyed participating in the Kubeflow training, which was held remotely. This training allowed me to consolidate my knowledge for AWS services, K8s, all the devOps tools around Kubeflow which are the necessary bases to properly tackle the subject. I wanted to thank Malawski Marcin for his patience and professionalism for training and advice on best practices. Malawski approaches the subject from different angles, different deployment tools Ansible, EKS kubectl, Terraform. Now I am definitely convinced that I am going into the right field of application.
Guillaume Gautier - OLEA MEDICAL | Improved diagnosis for life™
Course: Kubeflow
Adjusting to our needs
Sumitomo Mitsui Finance and Leasing Company, Limited
Course: Kubeflow
The details and the presentation style.
Cristian Mititean - Edina Kiss, Accenture Industrial SS
Course: Azure Machine Learning (AML)
Interactive, a lot of exercises
Edina Kiss, Accenture Industrial SS
Course: Azure Machine Learning (AML)
The Exercises
Khaled Altawallbeh - Edina Kiss, Accenture Industrial SS
Course: Azure Machine Learning (AML)
Very very competent trainer who know how to adapt to his audience, and to solve problems Interactive presentation
OLEA MEDICAL
Course: MLflow
the ML ecosystem not only MLFlow but Optuna, hyperops, docker , docker-compose
Guillaume GAUTIER - OLEA MEDICAL
Course: MLflow
Going through the notebooks, becoming more familiar with Qiskit and the various ways to do things.
Bank of Canada
Course: Practical Quantum Computing
I like that it focuses more on the how-to of the different text summarization methods
Course: Text Summarization with Python
AdaBoost Course Outlines
Course Name
Duration
Overview
Course Name
Duration
Overview
14 hours
This instructor-led, live training in the US (online or onsite) is aimed at data scientists and software engineers who wish to use AdaBoost to build boosting algorithms for machine learning with Python.
By the end of this training, participants will be able to:
- Set up the necessary development environment to start building machine learning models with AdaBoost.
- Understand the ensemble learning approach and how to implement adaptive boosting.
- Learn how to build AdaBoost models to boost machine learning algorithms in Python.
- Use hyperparameter tuning to increase the accuracy and performance of AdaBoost models.
Last Updated:
Upcoming AdaBoost Courses
AdaBoost Python for Machine Learning
12/13/2023 - 09:30
NY, Queens - Forest Hills Tower
14 hours
AdaBoost Python for Machine Learning
12/27/2023 - 09:30
NY, Queens - Forest Hills Tower
14 hours
AdaBoost Python for Machine Learning
01/10/2024 - 09:30
NY, Queens - Forest Hills Tower
14 hours
AdaBoost Python for Machine Learning
01/24/2024 - 09:30
NY, Queens - Forest Hills Tower
14 hours
AdaBoost Python for Machine Learning
02/07/2024 - 09:30
NY, Queens - Forest Hills Tower
14 hours
AdaBoost Python for Machine Learning
02/21/2024 - 09:30
NY, Queens - Forest Hills Tower
14 hours
AdaBoost Python for Machine Learning
03/06/2024 - 09:30
NY, Queens - Forest Hills Tower
14 hours
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