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Survey Report: How To Engage Machine Learning Developers
Survey Report: How To Engage Machine Learning Developers

Survey Report: How To Engage Machine Learning Developers

Published Updated

Key takeaways

  • Organisations often apply generic strategies to engage ML developers, overlooking their unique needs.
  • The rapid pace of innovation in machine learning creates challenges for developers to stay current.
  • ML developers require support not just technically, but also in areas like statistics and mathematics.
  • The Machine Learning Developers Summit 2020 highlighted the importance of collaboration and sharing insights within the ML community.
  • Survey insights revealed preferences in training formats and platforms for ML developers across varying experience levels.
5 min

A lot of organizations seek to engage closely with ML developers, either to increasing product adoption or crowdsource innovation. But a lot of these efforts fall into the trap of “seen-it-done-it-all” trap, where organizations employ the same strategies to engage them which they have utilized for other developers.

Machine Learning developers have unique needs from the ecosystem. They face challenges that developers from another stream are largely insulated from. Firstly, ML is a fast-changing domain. The rate of innovation currently is extremely high for some of the top developers to keep pace with. A state-of-art innovation project that you are working on for months, just got redundant because someone open-sourced a complete library for it.

Secondly, ML developers need handholding from not just the technical aspect but from a myriad of other fields like statistics, mathematics etc. This unique need makes them lookout for content and engagement from a different lens.

This year’s edition of the Machine Learning Developers Summit or MLDS 2020 brought together India’s leading Machine Learning innovators and practitioners who shared ideas and experiences about artificial intelligence (AI) and machine learning (ML) technologies, and developments in the AI/ML space.

MLDS 2020, held in Bangalore and Hyderabad in January 2020, was well attended and received by the Developer community. A survey was launched to all participants to gauge the pulse of ML developers and the larger developer community – the survey covered questions that helped gain insights on the critical needs of the larger developer ecosystem, including the training formats the developer prefer, the platforms the developers favor to interact and collaborate on, and so on. The survey respondents covered students, research scholars, and novice to senior-experienced professionals. The average work experience of the respondents of the survey was 7.4 years.


KEY FINDINGS

  • Critical Needs of Developer Community

Two of the most critical needs identified by the community were Information on What is happening in the Industry and Training on Latest Tools & Technologies, with 81.1% preferring both these 2 options – highlighting the need for awareness of tools/technologies and correspondingly skills and capability building – both critical in a rapidly evolving technology environment. This is followed by Networking with the Ecosystem at 62.2% and Showcasing Capabilities at 59.5%


  • Preferred Formats for Training on Latest Tools

The most favored format for training on the latest tools is Hybrid: Self + Assisted, with 78.4% preferring this option, which is a combination of the next two options - Self-learning at 32.4% and Assisted Learning at 8.1%.


  • Preferred Self-learning Avenues

The self-learning avenue most preferred by the community is Online Content, with 81.1% preferring this format. This was followed by Online forums to discuss, engage, and learn – in short collaborative self-learning at 59.5%, and Purchasing Books at 21.6%


  • Favored Platforms for Online Content for Self-learning:

The platforms for Online Content for self-learning favored by the participants are Online Courses, such as LinkedIn, Coursera, & others, with 97.3% of the participants preferring this avenue. 70.3% of participants prefer video format of Youtube for self-learning online content, while 37.8% of participants prefer Webinars as the avenue of self-learning. 


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