Meet our Community Champions for this week!

Thanks a lot for this recognition @Elena_Kosourova ! :smiley:

2 Likes

I am glad for all of you:

@aarong98104, @jesmaxavier , @sv.dolgushina , @sahiba.kaur.stats , @israelogunmola and… @Elena_Kosourova

As soon as I can, I will see them.

Thank you very much to everyone especially to our dear Elena.

A&E Happy Coding.

6 Likes

Thank you, dear Elena!
So inspiring)

3 Likes

Thanks, @Elena_Kosourova for the consideration! Congrats to all the other winners! :rocket: :trophy:

You guys are doing a great job!

3 Likes

Thank you @Elena_Kosourova and the rest of the community. I’m really happy being able to explore new skills and data while gaining insight, pointers and positive feedback from so many of you. What a cool experience. I can only hope to be able to give back as much as I’ve received. Have a great week everybody!

1 Like

Here are the Community Champions for this week: :tada:

Individual Project sharer:

@Johnsonk51502 shared his personal project on Pitchfork Over the Years where he dug deep into the data on the trends of reviews of the music website Pitchfork over time. The project has informative and easy-to-follow storytelling supported by gorgeous eye-catching charts, and a curious conclusion.

Dataquest Project sharers:

  • In her project on Building a Spam filter with Naive Bayes, @analuizallmp demonstrated her curiosity about the data using not only naive Bayes as per instructions but also the scikit-learn library. What’s more, Ana explored the cause of false positives and discussed the advantages and disadvantages of the Naive Bayes algorithm.

  • @sahiba.kaur.stats shared a project on I-94 Traffic Indicators that stands out for its perfect structure, thorough data analysis (especially traffic exploration based on the temperature and holidays), plenty of insightful plots, and efficient emphasis on the most important points.

  • @vishallbabu5 shared a well-structured project on Profitable App Profiles for the App Store and Google Play Markets that demonstrates a detailed description of each step of work, smooth storytelling supported by clean and easy-to-read code, and an interesting conclusion.

Project reviewers:

@Jesmaxavier and @Johnsonk51502, together with our Community Moderators, did an awesome job reviewing other learners’ projects and giving them helpful suggestions.

Useful resource sharers:

@vishallbabu5 shared an elegant alternative to the str.format method and @Edelberth shared even 3 useful resources: Flatpak vs Snap, API input parameters, and Free APIs (Cat Facts are really cool! :heart_eyes_cat:)

Great question asker:

@mr.sha3ban asked a very curious and tricky question. Check it here, together with the answer from @Bruno!


Thanks a lot, guys, for your enthusiasm and participation in our Community! :heavy_heart_exclamation:

I am proud to reward you with:

  • A 7 day extension on your current Dataquest subscription :rocket:
  • An exclusive Community Champion badge in our Community :medal_sports:
7 Likes

Congrats to all

:wink:

A&E.

6 Likes

Oh my god! Wasn’t expecting this at all. Made my day. Thank you, @Elena_Kosourova

3 Likes

Thanks a lot, @Elena_Kosourova . This motivates me to work harder.
Thanks too @jesmaxavier for reviewing my project in detail. I have not come across such an involved online community before.

3 Likes

Congrats, good people!

2 Likes

Here are the Community Champions for this week: :tada:

Individual Project sharers:

  • @gbpignatti5 shared a project on Comparing NBA and Euroleague Basketball, where he collected basketball data from two websites, cleaned, and analyzed it. The project is perfectly structured and demonstrates very profound data analysis, cool storytelling, elegant code, excellent documentation, and outstanding plots.

  • @jacqisbackyessheis shared a project on KNN to Predict Age of Abalone where she explored a very curious and original idea, gave the necessary background information about abalone marine snails, and analyzed various combinations of features before selecting the best one.

  • @ale-kor02 shared his advanced project on Optimum Transformers that you can install, import, and use for accelerated NLP pipelines with Infinity speed on CPU and GPU. The module is based on Transformers, Optimum, and ONNX runtime, the detailed project description and all the necessary files and links are here.

Dataquest Project sharers:

  • @jasperquak shared a project on Analyzing CIA Factbook Data Using SQL where he briefly but comprehensively illustrated curious statistics about countries using clean code, clear and informative explanations, and compelling storytelling.

  • @vishallbabu5 shared a project on Exploring Hacker News Posts that shows a great example of code documentation, a comprehensive conclusion, and a convenient description of dataset columns in tabular form.

  • The project of @alvaro.viudez on Finding Heavy Traffic Indicators stands out thanks to its straight-to-the-point storytelling, helpful plots that support the conclusions, and interesting analysis of some weather factors such as rain and snow.

Project reviewers:

@nathalia.pignaton and @Johnsonk51502, together with our amazing Community Moderators, were of great help to the Community by looking through other learners’ projects and providing them valuable feedback.

Useful resource sharer:

@Edelberth shared an interesting article on Data Science On The Linux Command Line and a useful resource on how to write formulas in Markdown.

Great question asker:

@mr.sha3ban offered to our Community two more cool and tricky Python challenges to think over. Check them both here and here.


Thanks a lot, guys, for your enthusiasm and participation in our Community! :heavy_heart_exclamation:

I am proud to reward you with:

  • A 7 day extension on your current Dataquest subscription :rocket:
  • An exclusive Community Champion badge in our Community :medal_sports:
11 Likes

Thank you and congratulations to others, too. :smiley:

2 Likes

That’s a nice surprise! :smiley: Thank you, and congratulations to others as well!

1 Like

Congratulations to all! :heart:

1 Like

I didn’t know about these recognitions!! That was a nice moral boost!! Thanks @Elena_Kosourova !! :slight_smile:

1 Like

Thanks a lot for the recognition!
After a long time happily receiving great reviews to my projects, I’m starting this new learning assistant path :sparkles:
Now I’m feeling ready and motivated to give it back to the community! :smiling_face_with_three_hearts: :rocket:

3 Likes

Happy to see you again among us, Nathalia, welcome back! :heavy_heart_exclamation: :partying_face: I remember your cool guided projects, you were the Community Champion for them too! Looking forward to seeing you around in the Community, with further reviews, projects, and other productive engagement with other learners! :star_struck:

3 Likes

congratulations to all of them, one day I’d be one of the monthly winners ahah

1 Like

Here are the Community Champions for this week: :tada:

Individual Project sharer:

@sv.dolgushina shared her first independent project on Car Market in Russia, Dynamics and Current Situation where she explored an interesting and fresh topic, conducted very professional data analysis, developed smooth storytelling supported by informative and eye-catching plots.

Dataquest Project sharers:

  • @radiofireworks shared an outstanding project on Popular data science questions that has a capturing title, perfect project structure, excellent storytelling supported by amazing charts, efficient emphasis on the most important points, and insightful conclusions.

  • @jasperquak shared his project on Answering Business Questions Using SQL where he applied his persistence to obtain accurate results and make the code format consistent. What’s more, Jasper used the helpful suggestion from @jithins123 about the scrollable output and updated his notebook accordingly! :star_struck:

  • @alvaro.viudez demonstrated light-speed and high-quality project making by sharing 2 projects this week: Storytelling Data Visualization on Exchange Rates and Clean and Analyze Employee Exit Surveys. The first one stands out for its step-by-step data exploration and clean and meaningful final graph, the second one – for its laconic but informative explanations and easy-to-read code.

  • @sahiba.kaur.stats, another light-speed learner of our Community, shared her project on Employee Exit Survey where she conducted profound data analysis, created insightful plots (the exploration of resignation by various factors, employment status, and year of resignation is really cool! :dizzy:), gave detailed conclusions and recommendations for the institutes.

  • @biengioichantroi shared their first data visualization project on Finding the indicators of heavy traffic in I-94 that stands out for its comprehensive description of the data along with interesting observations at each step of the project, and clear conclusions.

Project reviewers:

@WilfriedF and @madtitan, together with our amazing Community Moderators, were of great help to their peers by providing them productive interaction on their projects and giving constructive feedback.


Thanks a lot, guys, for your enthusiasm and participation in our Community! :heavy_heart_exclamation:

I am proud to reward you with:

  • A 7 day extension on your current Dataquest subscription :rocket:
  • An exclusive Community Champion badge in our Community :medal_sports:
8 Likes

Thanks a lot for this @Elena_Kosourova !

2 Likes