MLconf is a premier conference in machine learning for the industry. The proposed talks cover the following areas
- Algorithms that have graduated academic conferences such as NIPS,ICML, etc and have proven to be effective, robust and scalable in production
- Novel datascience practices, such as data transformations, new data sources, novel representations, etc
- Machine Learning/Data science case studies (Lessons learned), demonstrating challenges in the wild and how to handle them in a new way
- New platforms, tools for machine learning. Emphasis should be given on the technical challenges, benchmarks and motivation for the development
- New business practices, for managing, growing data science teams and expanding machine learning to new domains
- Tutorials and novel ways of presenting and simplifying machine learning domains, including: deep learning, kernel methods, bayesian nonparametrics, tensor algebra, etc
- Up and coming areas of machine learning that you think will dominate the industry in the future, such as probabilistic programming etc.
Submit your abstracts or draft presentations by February 4th. The selection of the presentation will be based on:
- Clarity and novelty of the presentation
- Diversity of the topics for the conference
- Speaker’s experience and reputation in the industry
- Limit your abstract to 500 words
- Try to submit a draft of your presentation by February 4th. This will make the work of the reviewers easy as it will help us understand the topic better as well as your ability to present the subject.
- Feel free to include supplementary material such as video/audio clips as well as reference papers. Put them all in a zip file and upload them
- Along with your presentation submit 5 multiple choice questions that would test the attendees comprehension of your presentation. MLconf offers a quiz after the day of the event that certifies attendee’s comprehension of the conference
