Simplify Experimentation, Deployment and Collaboration for ML and AI Models

Machine Learning and AI are changing or would say have changed the way how businesses used to behave. However, the Data Science community is still lacking good practices for organizing their projects and effectively collaborating and experimenting quickly to reduce “time to market”.

During this session, we will learn about one such open-source tool “DVC”
which can help you in helping ML models shareable and reproducible.
It is designed to handle large files, data sets, machine learning models, metrics as well as code

 
 

Outline/Structure of the Demonstration

5 Minutes - Why experimentation, Deployment, and reproducibility are need of hour and define 'DVC'

5 Minutes - Setup, Features and WorkFlow of DVC tool

10 Minutes - What all are the Use Cases followed by Demo

Learning Outcome

People will be able to learn how to leverage the software engineering principles we learned and how to apply it into the Data Science world and how we can simplify the workflow so that ML and AI models can run at large scale

Target Audience

Data Scientist, Data Engineers, Data Managers

Prerequisites for Attendees

On the concept side they should be knowing how the model development, deployment workflow works, its challenges.

On the tooling side they should be knowing Python, Git etc.

schedule Submitted 1 year ago

Public Feedback

comment Suggest improvements to the Author
  • Kuldeep Jiwani
    By Kuldeep Jiwani  ~  5 months ago
    reply Reply

    Hi Kuldeep,

    Your both proposals (this and other one) are focused on an interesting industry topic and both are really good quality. The program committee wanted to know that is it possible that you can combine the two proposals. Like in one part you can talk about the general things on how to do production deployment and another part could be focused on DVC sharing your experiences. This way we can the best of both and would make it highly interesting for the audience.

     

    • Kuldeep Singh
      By Kuldeep Singh  ~  2 months ago
      reply Reply

      Hi Kuldeep, Review members - Thanks a lot for accepting the proposal. As per suggestion we are merging two sessions, So could you update the time slot to 40-45 Minutes as well

    • Kuldeep Singh
      By Kuldeep Singh  ~  5 months ago
      reply Reply
      Hi Kuldeep,

      Yes we can do that as both are part of ‘Operationalizing the ML’ and more popularly ‘MLOps’.

      Let me know if some more info is needed.
      --00000000000011c2b805a5265960--
  • Deepti Tomar
    By Deepti Tomar  ~  6 months ago
    reply Reply

    Hello Kuldeep,

    Thanks for your time and efforts on the proposal! Could you answer the following questions to help the program committee understand your proposal better?

    • Are these demo(s) /use case(s) from your project work (industry-specific use cases)? Speaker's experience on the project helps people understand the concept better.
    • Did you use these techniques to help solve a particular problem? 
    • If yes, would you be sharing the Challenges faced in the implementation of the technique in your application and the workarounds?

    Thanks,

    Deepti

    • Kuldeep Singh
      By Kuldeep Singh  ~  6 months ago
      reply Reply

      Hi Deepti,

      Yes, There will be demo, these are from project work and needed once you move "experimentation  to production".
      A particular problem was solved for "Deployment and Collaboration, yes I can share the challenges learned over time and what other tools you can use to overcome it.

      • Kuldeep Jiwani
        By Kuldeep Jiwani  ~  6 months ago
        reply Reply

        Hi Kuldeep,

        Can you please elaborate on some of the challenges faced and what kind of solution did you deploy to resolve them.

        • Kuldeep Singh
          By Kuldeep Singh  ~  6 months ago
          reply Reply

          Hi Kuldeep, 

          Thanks

          On the issues side it was more how DVC is designed as it requires you to run the 'git' steps and then 'dvc' steps if gets missed out it does not notify and stale issues occurs. On the 'git' branches side some best practises were followed. i.e PR Model, Short lived feature branches.

          on the integrations side Dependency and run time environment consistency was achieved with Docker, For the checks to run continuously it was integrated with  CICD tool.

      • Deepti Tomar
        By Deepti Tomar  ~  6 months ago
        reply Reply

        Thanks for your response, Kuldeep! We will let you know in case if we have more questions.

  • Dr. Santonu Goswami
    By Dr. Santonu Goswami  ~  7 months ago
    reply Reply

    Hi Kuldeep, 

    Thank you for submitting your proposal to speak about DVC. 

    I have a few suggestions for you to improve on the overall submission:

    • In the Outline/Demonstration, please remove the first two paragraphs and provide itemized time-usage/strucutre of the talk. 
    • In the Links section, instead of just adding couple of urls, I suggest that you put the context to the url, i.e. what is this url about?

    I look forward to your response. 

    Thanks, 

    Santonu

     

    • Kuldeep Singh
      By Kuldeep Singh  ~  7 months ago
      reply Reply

      Thanks Santonu, suggestions has been implemented, let me know if some more things needed

  • Natasha Rodrigues
    By Natasha Rodrigues  ~  7 months ago
    reply Reply

    Hi Kuldeep,

    Thanks for your proposal! Requesting you to update the Outline/Structure section of your proposal with a time-wise breakup of how you plan to use 20 mins for the topics you've highlighted?

    Also, in order to ensure the completeness of your proposal, we suggest you go through the review process requirements.

    Thanks,

    Natasha"

    • Kuldeep Singh
      By Kuldeep Singh  ~  7 months ago
      reply Reply

      Thanks Natasha, Updated it, let me know if anything else needed from my side.

      • Natasha Rodrigues
        By Natasha Rodrigues  ~  7 months ago
        reply Reply

        Thanks Kuldeep, will let you know if we need more details.

        Regards,

        Natasha 


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