Introduction to AutoML

🎟 Register on Crowdcast for this online event
https://www.crowdcast.io/e/introduction-to-automl

AutoML is a very active area of AI research in academia as well as R&D work in industry. The public cloud vendors each promote some form of AutoML service. Tech unicorns have been developing AutoML services for their data platforms. Many different open source projects are available, which provide interesting new approaches. But what does AutoML mean?

Ostensibly automated machine learning will help put ML capabilities into the hands of non-experts, help improve the efficiency of ML workflows, and accelerate AI research overall. While in the long-term AutoML services promise to automate the end-to-end process of applying ML in real-world business use cases, what are the capabilities and limitations in the near-term?

🎓 What will you learn?

• Learn about the different kinds of AutoML techniques that are currently used
• Learn about the capabilities and limitations of AutoML in the near-term, as well as research efforts in progress
• Learn about available open source libraries for working with AutoML techniques
• Learn about how to leverage this area of technology to improve the end-to-end lifecycle for machine learning workflows
• In the interactive lab portion, we will review coding samples that compare use of different open source projects for AutoML.

👩‍💻 Who should attend?
Python developers with some background in machine learning will be able to try coding examples that use AutoML in the interactive lab portion of the program.

However everybody interested in machine learning applications is welcome to attend the lecture portion!

🎙 Speaker
Paco Nathan, expert in data science, natural language processing, machine learning and cloud computing, https://derwen.ai/paco

🎟 Register on Crowdcast for this online event
https://www.crowdcast.io/e/introduction-to-automl