Announcing the Community Champions for this week!

That’s a great news @nityesh, thanks a lot! :grinning:
For me the DQ Community is a great resource to exchange ideas with other enthusiastic students, help them and get helped, find the room for improvement, which is not so easy to notice when learning alone.

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The Community has helped a lot in my learning. Also through guided projects, I get to learn new ways of coming up with informative and amazing data science projects. I also get to share my knowledge/skills to the community members to help them unblock the difficulties they are facing.

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Congraluations everyone :tada:

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Congratulation all Champions…! :trophy: :medal_sports:

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Congratulations champions! You make this community better :smiley:

Happy coding :smile:

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It is so amazing to see strangers, sitting worlds apart and having an impact on each other’s learning! That’s what our Community Champions were doing this week:

Personal Project sharers:

  • @animus.agbor shared their exciting personal project - Malaria Detection using Deep Learning. In this project, Animus tries to tackle the ambitious task of identifying whether a Red Blood Cell has been infected by Malaria parasites using neural networks.

    Also worth noting is the conversation that @animus.agbor and @WilfriedF had in that thread which allowed Animus to improve on their project!

  • @veratsien shared their attempt at coding a neural network model from scratch to build a digit classifier. As of now, this project is incomplete because of an unexpected issue with the scipy.optimize library.

    Can someone help them?

Most liked:

  • @moriturus7 shared an alternative to using Selenium for web scraping - Playwright.

    Despite its popularity, Selenium has quite a lot of disadvantages like poor scalability. Playwright is an alternative.

    That’s why I want to tell you about the library, which is quite famous among JS developers, but so far little known in the Python community.

    Max has become our community’s expert on web scraping as is evident from their detailed conversations about various web scraping solutions in various threads throughout the Community. This gives this post special credibility! Do check it out if you’re interested in web scraping.

Alternative solutions:

Guided Project sharers:

  • @adrianzchmn has shared another one of their beautiful projects with our community - Visualizing Earnings Based On College Majors. It has great analysis and beautiful visualizations. What more - they were also able to make multiple improvements to it based on @htw’s feedback!

  • @Andy shared an excellent Guided Project analyzing Hacker News posts. I love how Andy cared enough to format the outputs so they render pretty.

    This is my fourth week on Dataquest, and am having lots of fun learning to code around data! I started with absolutely no knowledge on coding, but have already learned so much in that short period of time. Dataquest is an exceptional platform with an amazing community!

    Awesome progress, Andy! :heart_eyes:

Guided Project reviewers:

This week our Guided Project sharers benefited from the excellent, actionable feedback provided by @htw and @chris_is_working! Thank you so much for your time, folks.

I’m so proud of the little community of Data Science learners that we are creating here! :heavy_heart_exclamation:

Thank you Champions for contributing to it. I appreciate your participation and would love to give y’all:

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


Before you go Champions, can you tell us - What’s one thing you learned last week that you didn’t know before?

Please share your answer by replying below! :smile:

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@nityesh Thank you for the shoutout. I’m a little embarrassed since it’s an unfinished project and I haven’t gotten back to it.

I’m not the first one to attempt this particular project so I was able to look up other approaches, it seems all of them are not generalized, i.e. the number of hidden layers and number of neurons are pre-determined and specified for the model. After a little digging, I think it’s because the underlying code of scipy.optimize.fmin_cg requires unpacking the weights from its vector form as the parameter. I did try to build the model with a specified hidden layer and neurons, the cost function did work but again the derivative function didn’t. I would greatly appreciate any help or input.

I am glad that I started this project though. If anything, the attempt of the project alone helped me in understanding neural network models better and I really enjoyed the math behind it.

In conclusion, I would appreciate any help or insight anyone can provide on this project. Also, it definitely makes me appreciate machine learning libraries like scikitlearn a lot more. What a time to be alive! :joy:

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Well done champions! I would like to thanks @moriturus7 for sharing the Playwright library, it’s a nice project going on. I’m quite interested in web-scraping too (I’m actually working on my personal project withBeautiful Soup at the moment).

Well done @htw and @chris_is_working! Leaving feedback is extremely useful both for you and for people receiving it, we learn much-much better this way.

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Hi, @artur.sannikov96

If you have any problems with Beautiful Soup or with the approach to the source through requests, which you probably use in conjunction with Beautiful Soup. You can write me a personal message and I will give you my recommendations for the solution.

Although I prefer to use LXML instead of Beautiful Soup

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@nityesh

Thank you very much! I am glad if my feedback helps others.

I guess participating in the discussions is partly due to the joy of helping others to solve problems and improve their coding skills, but it also helps my own progress, when I review code, think about alternative solutions and figure out why certain implementations don’t work or lead to the wrong results.

Best
htw

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I know, right. Amen to that! :joy:

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Thank you for the recognition @nityesh! Thank you @htw for helping me improve my project!
And congratulations everyone!

What’s one thing you learned last week that you didn’t know before?
The use of itertools, courtesy of @htw

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Congratulations Everyone! :tada:

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Here are our newest Community Champions: :tada:

Personal Project sharers:

Guided Project sharers:

Guided Project reviewers:

I also want to call out @WilfriedF and @jithins123 for the excellent feedback that they leave on Guided Projects shared by our community. Thank you for lifting up your peers!

And thank you everyone! :heart:

I am happy to give you:

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


Before you go Champions, can you tell us - what is one thing that you learned last week that you didn’t know before?

Please share your answer by replying below! :smile:

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Thank you for this amazing news @nityesh and congratulations to all the champions! :partying_face: One of the new things I learned this week was how to deal with SettingWithCopyWarning and RuntimeWarning. So now I don’t have anymore those scaring red rectangulars in my projects! :grinning:

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Thanks a lot Nityesh for this great news and congratulations to fellow champions. I this week I was fortunate enough to receive some amazing feedback on my guided projects which is definitely great.

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Congratulations Champion :partying_face: :partying_face:

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Please join me in congratulating our latest cohort of our Community Champions: :tada:

Most liked:

  • @ananth.ch got a unique opportunity to jump on a call with a Data Scientist and asked him lots of interesting questions. Ananth was kind enough to take notes and share them with our community!

    Check them out - lots of wisdom in there.

  • @vinodgchandaliya asked an interesting question to our community - How to build a live data science projects? @moriturus7 gave them wonderful advice. They connected our Guided Projects to the real world tasks and also laid down some steps to follow if you want to get more serious.

    Do join the conversation with your own thoughts and perspectives.

Guided Project sharers:

Guided Project reviewers:

Finally, I want to call out @veratsien and @artur.sannikov96 for generously providing really helpful feedback to strangers around the world.

Thanks Champions for giving life to our little community! :heart:

I am glad to give you:

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


Before you go Champions, can you tell us - What is the number #1 reason you come back to the Community?

Please share your answer by replying below! :smile:

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@nityesh Thank you for the recognition! I definitely get a lot of satisfaction from being able to help others. And it’s one of the many reasons I come back to the community frequently.

I think the #1 reason for me to come back to the community is a sense of comradery. Self-learning is not like school, you take full responsibility for the initiative, accountability, and progress. It’s a lonely journey for the most part. But this community is one of the best in my experience, with a culture of helping each other, sharing generously, and recognizing the efforts of everyone in the community.

Great work as always everyone! Let’s keep it up. :vulcan_salute:

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Thanks for the recognition!

Recently I don’t write that much on the community due to the lack of time (and I’m also finishing up my own personal project) but I really try to keep up with the reviews because as always I strongly believe in feedback systems that encourage us to constantly improve in our data science journey!

@vinodgchandaliya I really liked that you asked this question: I was also thinking about some real-time live system that will serve people for many months if not years:)

I could also try to build something similar for the non-profit organization I volunteer in (we have pretty many repetitive tasks to do, even though I partially automated them with Google Sheets standard formulas) but I can only imagine what I can do with the power of Python:) Maybe I should try!

Happy coding everyone :smile:

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