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Machine Learning with Random Forest

14 Hours
This instructor-led, live training in Los Angeles (online or onsite) is aimed at data scientists and software engineers who wish to use Random Forest to build machine learning algorithms for large datasets. By the end of this training, participants will be able to:
  • Set up the necessary development environment to start building machine learning models with Random forest.
  • Understand the advantages of Random Forest and how to implement it to resolve classification and regression problems.
  • Learn how to handle large datasets and interpret multiple decision trees in Random Forest.
  • Evaluate and optimize machine learning model performance by tuning the hyperparameters.
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Testimonials (26)

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Francesco Ferrara
Course - Introduction to Machine Learning

The trainer showed that he has a good understanding of the subject.

Marino - EQUS - The University of Queensland
Course - Machine Learning with Python – 2 Days

It was a great intro to ML!! I liked the whole thing, really. The organization was perfect. The right amount of time for lectures/ demos and just us playing around. Lots of topics were touched, just at the right level. He was also very good at keeping us super engaged, even without any camera being on.

Zsolt - EQUS - The University of Queensland
Course - Machine Learning with Python – 2 Days

Clarity of explanation and knowledgeable response to questions.

Harish - EQUS - The University of Queensland
Course - Machine Learning with Python – 2 Days

The knowledge of the trainer was very high and the material was well prepared and organised.

Otilia - TCMT
Course - Machine Learning with Python – 2 Days

I thought the trainer was very knowledgeable and answered questions with confidence to clarify understanding.

Jenna - 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 - 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

Keeping it short and simple. Creating intuition and visual models around the concepts (decision tree graph, linear equations, calculating y_pred manually to prove how the model works).

Nicolae - DB Global Technology
Course - Machine Learning

It helped me achieve my goal of understanding ML. Much respect for Pablo for giving a proper introduction in this topic, since it becomes obvious after 3 days of training how vast this topic is. I have also enjoyed A LOT the idea of virtual machines you have provided, which had very good latency! It allowed every coursant to do experiments at their own pace.

Silviu - DB Global Technology
Course - Machine Learning

The way practical part, seeing the theory materializing into something practical is great.

Lisa Fekade - Vodacom
Course - Machine Learning

It's just great that all material including the exercises is on the same page and then it gets updated on the fly. The solution is revealed at the end. Cool! Also, I do appreciate that Krzysztof took extra effort to understand our problems and suggested us possible techniques.

Attila Nagy - 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

Interesting knowledge

Gabriel - MINDEF
Course - Machine Learning with Python – 4 Days

The trainer was a practitioner with a lot of experience and had a very good knowledge of the material.

Witold Iwaniec - City of Calgary
Course - Machine Learning with Python – 4 Days

The way of transferring knowledge and the knowledge of the trainer.

Jakub Rękas - Bitcomp Sp. z o.o.
Course - Machine Learning on iOS

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

Szkolenie rewelacyjne, jedno z najlepszych, na jakich bylem! Prowadzacy Rafal doskonale odpowiadal w zakresie poruuszanych zagadnien, bardzo dokladnie tlumaczyl wszystkie metody. Jestem bardzo zadowolony i chetnie ponownie skorzystam ze szkolenia prowadzonego przez tego szkoleniowca.

Darek Paszkowski - Orange Szkolenia Sp. z o.o.
Course - Feature Engineering for Machine Learning

Rysunki na flipcharcie, całe szkolenie.

Kasia Nawrot - 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

The details and the presentation style.

Cristian Mititean - Accenture Industrial SS
Course - Azure Machine Learning (AML)

The Exercises

Khaled Altawallbeh - Accenture Industrial SS
Course - Azure Machine Learning (AML)

the ML ecosystem not only MLFlow but Optuna, hyperops, docker , docker-compose

Guillaume GAUTIER - OLEA MEDICAL
Course - MLflow

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