MLH brought me here !

SarraLKSC — Mon, 11 Jan 2021 20:33:12 +0000

After my first post being about HacktoberFest, here i am again to share my experience and thoughts about another Hacker's event: Local Hack Day !

Local Hack Day, or LHD in short, is a computer science event organized internationally by Major League Hacking. It takes place thrice a year for it's 3 chapters : Learn, Build and Share.

Today I am here to talk about LHD: Build 2021 edition (still open if you want to join).
The key word this year for LHD:Build is CHALLENGE ! everyday from january 10th to january 18th, participants can enrol in coding challenges as easy as writing hello world in a new language or as fun as creating a tic tac toe game from scratch. In addition to these 24h challenges. We can also sign up for weekly challenges if we want to create bigger projects that involve computer vision or maybe build a playlist for parties app ... these are the topics that i personally am interested in but the list of challenges is long ( you can check them out here https://localhackday.mlh.io/build#ChallengesD )

I will probably upload my challenges in a repo so keep an eye out for my Github profile if you are curious ( https://github.com/SarraLKSC)

My HacktobereFest 2k20 experience

SarraLKSC — Mon, 23 Nov 2020 21:58:38 +0000

Almost 30 days after my 4th PR I am now finally writing this Dev article to share my HacktoberFest experience. This year I contributed to the famous month long celebration of open source for the first time ever and I can already tell that it’ll become a tradition for me.

My 4 PRs were submitted to the Micro Club’s HacktoberFest2k20 repo. The club’s repo was organized in a way that gathers projects, tutorials, and documentation. My contributions were added to the project directory and consisted in a number of jupyter notebooks that gave step by step [commenting your code is IMPORTANT] explanations of data visualization labs with matplotlib and machine learning lab with scickit-learn.
Data visualization was done on a recent dataset regrouping Covid 19 stats about cases (confirmed cases, deaths and recoveries) across different countries first as a table of data then as time-series which allowed the implementation of different plt representations (histograms, graphs, circles..).

For the Machine learning notebook, the goal was to predict flight delays using the RandomForestClassifier model available on sklearn.ensemble module. Once again each step was commented from loading the dataset and splitting it into the needed sets to the display of the test results.

Finally after my 4PRs were merged, I OF COURSE made my personalized Octocat that I call “killer next door” a female octocat that totally looks inoffensive …. But beware.

DEV Community: SarraLKSC

MLH brought me here !

My HacktobereFest 2k20 experience