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The way practical part, seeing the theory materializing into something practical is great.
Convolution filter
The trainer showed that he has a good understanding of the subject.
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.
Clarity of explanation and knowledgeable response to questions.
The knowledge of the trainer was very high and the material was well prepared and organised.
I thought the trainer was very knowledgeable and answered questions with confidence to clarify understanding.
Working from first principles in a focused way, and moving to applying case studies within the same day
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.
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).
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.
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.
I liked the lab exercises.
The trainer was so knowledgeable and included areas I was interested in.
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.
Interesting knowledge
The trainer was a practitioner with a lot of experience and had a very good knowledge of the material.
The trainer because he could handle almost every subject and situation.
The manner in which the trainer explained the concepts, his positive and welcoming attitude and the real-world examples provided for each exercise.
Very good training session with nice documentation and exercises and Kristian did it like a professional he is.
The way of transferring knowledge and the knowledge of the trainer.
That it was applying real company data. Trainer had a very good approach by making trainees participate and compete
The trainer was a professional in the subject field and related theory with application excellently
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.
Rysunki na flipcharcie, całe szkolenie.
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.
The details and the presentation style.
The Exercises
the ML ecosystem not only MLFlow but Optuna, hyperops, docker , docker-compose
