Course Outline
Introduction
- Kubeflow on OpenShift vs public cloud managed services
Overview of Kubeflow on OpenShift
- Code Read Containers
- Storage options
Overview of Environment Setup
- Setting up a Kubernetes cluster
Setting up Kubeflow on OpenShift
- Installing Kubeflow
Coding the Model
- Choosing an ML algorithm
- Implementing a TensorFlow CNN model
Reading the Data
- Accessing a dataset
Kubeflow Pipelines on OpenShift
- Setting up an end-to-end Kubeflow pipeline
- Customizing Kubeflow Pipelines
Running an ML Training Job
- Training a model
Deploying the Model
- Running a trained model on OpenShift
Integrating the Model into a Web Application
- Creating a sample application
- Sending prediction requests
Administering Kubeflow
- Monitoring with Tensorboard
- Managing logs
Securing a Kubeflow Cluster
- Setting up authentication and authorization
Troubleshooting
Summary and Conclusion
Requirements
- An understanding of machine learning concepts.
- Knowledge of cloud computing concepts.
- A general understanding of containers (Docker) and orchestration (Kubernetes).
- Some Python programming experience is helpful.
- Experience working with a command line.
Audience
- Data science engineers.
- DevOps engineers interesting in machine learning model deployment.
- Infrastructure engineers interesting in machine learning model deployment.
- Software engineers wishing to automate the integration and deployment of machine learning features with their application.
Testimonials
I really appreciated the crystal clear answers of Chris to our questions.
Léo Dubus
I generally enjoyed the knowledgeable trainer.
Sridhar Voorakkara
I was amazed at the standard of this class - I would say that it was university standard.
David Relihan
Very good all round overview. Good background into why Tensorflow operates as it does.
Kieran Conboy
I liked the opportunities to ask questions and get more in depth explanations of the theory.
Sharon Ruane
Very updated approach or CPI (tensor flow, era, learn) to do machine learning.
Paul Lee
Given outlook of the technology: what technology/process might become more important in the future; see, what the technology can be used for.
Commerzbank AG
I was benefit from topic selection. Style of training. Practice orientation.
Commerzbank AG
A wide range of topics covered and substantial knowledge of the leaders.
- ING Bank Śląski S.A.; Kamil Kurek Programowanie
Lack
- ING Bank Śląski S.A.; Kamil Kurek Programowanie
Big theoretical and practical knowledge of the lecturers. Communicativeness of trainers. During the course, you could ask questions and get satisfactory answers.
Kamil Kurek - ING Bank Śląski S.A.; Kamil Kurek Programowanie
Practical part, where we implemented algorithms. This allowed for a better understanding of the topic.
- ING Bank Śląski S.A.; Kamil Kurek Programowanie
exercises and examples implemented on them
Paweł Orzechowski - ING Bank Śląski S.A.; Kamil Kurek Programowanie
Examples and issues discussed.
- ING Bank Śląski S.A.; Kamil Kurek Programowanie
Substantive knowledge, commitment, a passionate way of transferring knowledge. Practical examples after a theoretical lecture.
Janusz Chrobot - ING Bank Śląski S.A.; Kamil Kurek Programowanie
Practical exercises prepared by Mr. Maciej
- ING Bank Śląski S.A.; Kamil Kurek Programowanie
Human identification and circuit board bad point detection
王 春柱 - 中移物联网
Demonstrate
- 中移物联网
About face area.
- 中移物联网
A lot of practical tips
Pawel Dawidowski - ABB Sp. z o.o.
A lot of information related to the implementation of solutions
Michał Smolana - ABB Sp. z o.o.
A multitude of practical tips and knowledge of the lecturer from a wide range of AI / IT / SQL / IoT issues.
- ABB Sp. z o.o.
I started with close to zero knowledge, and by the end I was able to build and train my own networks.
Huawei Technologies Duesseldorf GmbH
Organization, adhering to the proposed agenda, the trainer's vast knowledge in this subject
Ali Kattan - TWPI
the way he present everything with examples and training was so useful
Ibrahim Mohammedameen - TWPI
Very knowledgeable
Usama Adam - TWPI
The excersise where we should train a network to approximate a function
Nercia Utbildning AB
Tomasz really know the information well and the course was well paced.
Raju Krishnamurthy - Google
The trainer explained the content well and was engaging throughout. He stopped to ask questions and let us come to our own solutions in some practical sessions. He also tailored the course well for our needs.
Robert Baker
Trainer was very knowledgeable and open to questions, liked to draw diagrams and explained things in a pretty good way
Trainer was very knowledgeable and open to questions, liked to draw diagrams and explained things in a pretty good way