Looking to increase my connections

[mayurcodes01]

Introduce yourself

Hi everyone I am Mayur from India currently doing a post graduation under a program of masters of computer applications and I am here to learn new things and especially making techy connections and people who can guide me into tech

Links (optional)

No response

Where are you in your GitHub journey?

Looking for the latest developer trends

And where are you going next on GitHub?

Currently I am looking to connect with techy peoples also to improve my knowledge and my practical skills in a machine learning and especially about cyber security and LLM models

What technical skills or projects are you working on?

Working on softwares based projects with mostly python

Got a question for us? (optional)

No response

[yashh1323]

Welcome, Mayur. For ML and LLM work in Python, the easiest way to meet people is to find a small open source project you actually use and fix something minor in it, like a typo in the docs or a “good first issue” label. Cybersecurity is a bigger field, so pick one corner of it first.

[mayurcodes01]

Thanks i were thinking that contributing as a big part in a projects means contributions but i will have to look at smaller once too.

[ronitgupta138]

Hey Mayur! Best way to connect is to start contributing to active open-source tools or building small, focused repos in public:

1. Find beginner-friendly Python/ML repos with good first issue tags, or help reproduce bugs on active libraries.
2. Share what you're building on LinkedIn/X with short code demos or benchmarks — engineers love seeing real code and first-principles breakdowns.
3. Check out local dev meetups or college hackathons in your city. Good luck with the MCA!

[mayurcodes01]

Yeah that's a great way i will look for it

[Grit-77]

Hi Mayur — I work on small Python tools around coding agents. One concrete starter exercise for your Python/LLM interests is a tiny evaluation harness: fixed synthetic inputs, a deterministic expected result, and one deliberately wrong case that the checker must reject. Save the actual command output and exit status, rather than relying on the model saying it passed.

That gives you something small another developer can reproduce and review, without needing a large model-training project first. Are you more interested in command-line/testing tools or retrieval and memory for LLM applications?

Disclosure: Codex helped prepare this reply; this is a fellow builder's suggestion, not an official GitHub response.

[mayurcodes01]

yes grit, i like everything and every type of technical activity that can push me ahead to learn and implement .