What are some ways to give back after a machine learning mentorship?

Knowledge expands when we share it. We get inspired by LinkedIn articles when we come to know about any breakthrough in our field of interest and then we immediately try to gain some actual knowledge on it via the latest research papers or scholarly articles. Publishing and promoting your work is essential for your visibility, motivation, and as well as for inspiring others. Don't just keep your achievements and findings to yourself. Research is not for rusting of knowledge in your laptop.

A great way to contribute back to the ML community is to work on an open source project that allows you to share your skills and abilities with others as well as the knowledge you gained in the past. On top of that, it also leads to an improvement of your skills while working on such projects. This is something that anyone can do as well, whether you were self-taught or guided by a mentor.

Document your learning journey, the challenges you encountered and the lessons learned. This can be a valuable resource for beginners and those looking to deepen their knowledge. Get involved in online forums and communities: Join groups at LinkedIn, forums such as Stack Overflow, learning community or dedicated data science communities. Answering questions and participating in discussions can be incredibly helpful.

Contributing back to tech communities in general is almost the same: Give talks on a subject you are an expert in, help the technology improve by open-sourcing solutions you think people will be benefited from and make friends.

For instance, after learning about natural language processing (NLP) under a mentor, you could contribute a beginner's guide to NLP on a blog. This would help beginners grasp fundamental concepts while strengthening your own understanding. You could also cover more complex topics, like creating a thematic analysis using NLP, for those who are higher up in their learning curve. Continual sharing and learning deepens your expertise while aiding the broader development of the machine learning community.

Become a mentor yourself: Pass on your acquired knowledge and skills by supporting others as a mentor. This keeps the cycle of knowledge transfer going and contributes to the growth of the data science community.

This is something which is very close to my heart. I truly believe that human resource is the best resource. Supporting others by sharing your own story, networking, understanding their story and then helping according to their needs is important for the growth of the ML community (be it helping them connect with the right mentors, mentoring yourself, referring them, pointing them to the correct resources, etc.).

Be an active participant in forums, communities, or online platforms related to machine learning. Answer questions, provide advice, and assist others who are seeking help or guidance.

Contribute to open-source projects in machine learning. This could involve writing code, improving documentation, or helping with bug fixes, benefiting the wider ML community.

One of the best ways to give back is by contributing to open-source projects. This doesn't have to involve a large project. Small contributions, such as helping a model or framework work on a different platform, editing or translating documentation, and cleaning up datasets, are also valuable.

- Being a mentor as a Machine Learning enthusiast means imparting practical skills and knowledge from their industry experience to mentees who want to learn more about the field, such as data analysis, modelling techniques, data quality issues, and data matching methods - A machine learning mentor can offer guidance and advice to mentees who are facing challenges or difficulties in their learning journey, such as time constraints, data availability, ethical issues, or presentation skills. - machine learning mentor can use their industry experience to help mentees understand the impact and implications of their work on different groups of people, such as disabled children and their families, and how to advocate for their needs and rights.

Consider donating to organizations or initiatives focused on promoting education in machine learning, especially those that provide resources to underprivileged communities or support diversity and inclusion in tech.

The mentor and the mentee celebrating successes thus helps create a good rapport between them. At the same time, showing appreciation to your senior is an acknowledgement of their help along this path. One way to appreciate their contribution is to see what impact it has had upon your machine-learning journey.

Did you hear about the guy fooled LI algo once and is about to do it again tomorrow? Cheer for him mate! Great lad. G’day init?

Acknowledge and celebrate your growth and achievements. By showcasing your progress, you inspire others and demonstrate the possibilities in the field of machine learning.

Share data sets to support Hackathons and IT projects at universities: If you have collected interesting data for a project (subject to privacy and permissions), you should make it available (where permitted) for others to use in their research, projects, or Hackathons.

Share your success with your previous mentor, especially when the mentorship was informal and not part of a structured program. It's always nice to hear back, and even possibly connect new incoming mentees with "graduated" mentees who have become successfull peers.

With the peer and your network in the industry it would be more credible to build a network of mentors and mentees, and fostering a culture of collaboration and mentorship in the ML community can have many benefits. - Build trust and rapport among the members of the community - Increase the engagement and satisfaction of the participants - Enhance the skills and knowledge of both mentors and mentees - Promote innovation and diversity of ideas - Support the personal and professional growth of the participants - Writing blogs or articles about your insights and projects in ML - Collaborating with academic institutions to offer industry insights and close the gap between academia and industry as a STEM volunteer

One way to give back is to give credit to your mentor. Everyone likes to be appreciated, especially after helping out. Mentoring is no easy feat, especially if the mentee starts from scratch. The relationship with your mentor will go a long way if you do this.