Automated Machine Learning

This week I was invited to give a talk at the Haifa Tech Talks meetup. In this talk I presented an introduction to Automated Machine Learning (Auto ML).
I discussed some approaches to face the challenges of Auto ML, including Data Preprocessing, Hyperparameter Tuning and Algorithm Selection.
I also presented two popular tools for Auto ML: Auto-sklearn (based on Bayesian Optimization) and TPOT (based on Genetic Algorithms).

About the speaker:
Hayim Makabee has 25 years experience with Software Development, and in the last 10 years has specialized in the field of Data Science.
He is currently the CEO at KashKlik, an advanced Influencer Marketing platform.
Hayim provides consultancy and mentorship to startup companies in the fields of Machine Learning and Predictive Analytics.

You can see my slides and video below.

Here is the video of the talk (in Hebrew):

This talk was hosted by the Haifa Tech Talks meetup group. Special thanks to Roman Levin who organized the event.

About Hayim Makabee

Veteran software developer, enthusiastic programmer, author of a book on Object-Oriented Programming, co-founder and CEO at KashKlik, an innovative Influencer Marketing platform.
This entry was posted in Data Science, Machine Learning, Research and tagged , , . Bookmark the permalink.

1 Response to Automated Machine Learning

  1. Rohan Singh says:

    Automated machine learning (AutoML) is the process of automating the process of applying machine learning to real-world problems. AutoML covers the complete pipeline from the raw dataset to the deployable machine learning model.

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