MLOps Conference
The Fifth Elephant For members

MLOps Conference

On DataOps, productionizing ML models, and running experiments at scale.

Make a submission

Accepting submissions till 14 Jul 2021, 11:00 PM

Tickets

Loading…

Machine Learning (ML) is at the helm of products. As products evolve with time, so is the necessity for ML to evolve. In 2010s, we saw DevOps culture take the forefront for engineering teams. 2020s will be all about MLOps.

MLOps stands for Machine Learning Operations. MLOps mainly focuses on workflows, thought processes and tools that are used in creating ML models, and their evolution over time. The workflows for ML at organizations are different as the problem space, maturity of teams and experience with ML tools are widely different.

MLOps relies on DataOps. DataOps is about Data operations, and helps define data and SLOs for data - how they are stored, managed and mutate over time - thereby providing the foundations for sound ML. The success and failure of ML models depends heavily on DataOps, where data is well-managed and brought into the system in a well thought out manner. ML and data processes have to evolve to provide insights into the reasons as to why certain models are not behaving as before.

Productionizing ML models is a challenge, but so is running experiments at scale. MLOps caters not only to scaling ML models in production, but also helps in providing guidelines and thought processes to support rapid prototyping and research for ML teams.

MLOps Conference 2021 edition

The 2021 edition is curated by Nischal HP, Director of Data at Scoutbee.

The conference covers the following themes:

  1. Machine Learning Operations
  2. Machine Learning in Production
  3. Privacy and Security in Machine Learning
  4. Tooling and frameworks in Machine Learning
  5. Economies of Machine Learning

Speakers from Doordash, Twilio, Scribble Data, Microsoft Research Labs India, Freshworks, Aampe, Myntra, Farfetch and other organizations will share their experiences and insights on the above topics.

Schedule: https://hasgeek.com/fifthelephant/mlops-conference/schedule

Who should participate in MLOps conference?

  1. Data/MLOps engineers who want to learn about state-of-the-art tools and techniques.
  2. Data scientists who want a deeper understanding of model deployment/governance.
  3. Architects who are building ML workflows that scale.
  4. Tech founders who are building products that require ML or building developer productivity products for ML.
  5. Product managers, who are seeking to learn about the process of building ML products.
  6. Directors, VPs and senior tech leadership who are building ML teams.

Contact information: Join The Fifth Elephant Telegram group on https://t.me/fifthel or follow @fifthel on Twitter. For inquiries, contact The Fifth Elephant on fifthelephant.editorial@hasgeek.com or call 7676332020.

Hosted by

The Fifth Elephant - known as one of the best data science and Machine Learning conference in Asia - has transitioned into a year-round forum for conversations about data and ML engineering; data science in production; data security and privacy practices. more

Supported by

Scribble Data builds feature stores for data science teams that are serious about putting models (ML, or even sub-ML) into production. The ability to systematically transform data is the single biggest determinant of how well these models do. Scribble Data streamlines the feature engineering proces… more

Promoted

Deep dives into privacy and security, and understanding needs of the Indian tech ecosystem through guides, research, collaboration, events and conferences. Sponsors: Privacy Mode’s programmes are sponsored by: more

Milecia McGregor

@milecia

Tuning Hyperparameters with DVC Experiments

Submitted Jun 14, 2021

When you start exploring multiple model architectures with different hyperparameter values, you need a way to quickly iterate. There are a lot of ways to handle this, but all of them require time and you might not be able to go back to a particular point to resume or restart training.

In this talk, you will learn how you can use the open-source tool, DVC, to compare training metrics using two methods for tuning hyperparameters: grid search and random search. You’ll learn how you can save and track the changes in your data, code, and metrics without adding a lot of commits to your Git history. This approach will scale with your data and projects and make sure that your team can reproduce results easily.

Comments

{{ gettext('Login to leave a comment') }}

{{ gettext('Post a comment…') }}
{{ gettext('New comment') }}
{{ formTitle }}

{{ errorMsg }}

{{ gettext('No comments posted yet') }}

Make a submission

Accepting submissions till 14 Jul 2021, 11:00 PM

Hosted by

The Fifth Elephant - known as one of the best data science and Machine Learning conference in Asia - has transitioned into a year-round forum for conversations about data and ML engineering; data science in production; data security and privacy practices. more

Supported by

Scribble Data builds feature stores for data science teams that are serious about putting models (ML, or even sub-ML) into production. The ability to systematically transform data is the single biggest determinant of how well these models do. Scribble Data streamlines the feature engineering proces… more

Promoted

Deep dives into privacy and security, and understanding needs of the Indian tech ecosystem through guides, research, collaboration, events and conferences. Sponsors: Privacy Mode’s programmes are sponsored by: more