Reviewing Your Data Science Projects - Episode 11(GITHUB CLEANING)

In this video I review the data science projects in Shivam's github profile. Special thanks to him for submitting his work!

Shivam is very active on github which is a good thing. Still, his github profile could use some maintenance. He has some repos that are empty and should be deleted. He could also benefit from improved naming conventions and project descriptions.

One of my favorite projects that he does is he coded a Nerual Net from scratch. This is an awesome project that shows his genuine interest in how the data science models work. This isn't something that I look for, but it is definitely a positive to have. This isn't a data science project that would supplement for one done with actual data, but it is still very strong.

Machine learning projects I recommend doing: At least 1 on regression, classification, clustering. An additional project on deep learning, computer vision, or NLP.

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[Mario-oxdm]

I'm almost ready to submit my projects/portfolio to this series! Another great review video Ken!

[ImportData]

Thanks, Ken for sharing my video! I agree with you about linking projects on the GitHub profile page. That will help employers view your projects more readily! 😄

[Dynamite_mohit]

First, great video and definitely a great series Ken.

In few weeks i will be ready to submit my github.
Merging all the recommendation given by Ken Jee.

Can't wait :)

[rayojel]

Hey bro, just wanted to let you know that 6 months of studying later, I may have a job lined up! I did the interviews and skills tests just waiting on the word. Fingers crossed 🤞🏽

[thomasgeorgethomas]

As usual, great content and pragmatic tips! Thanks for doing this. Hoping one day to get my projects reviewed! This might be slightly out of place but I have been meaning to ask about your ring, It's prominent and elegant and I was wondering where can I get myself one of those :P

[arthurmlcc]

Hey ken! Loving the series! I wanted to make a suggestion since I don't have a decent portfolio yet to submit it for your analysis. I think you should make a series solving actual data science tasks and problems that Data Scientists face daily. I think it would be very innovative and helpfull to beginners like me. Greeting from Brazil!

[DataProfessor]

Thanks Ken for another great video! Noticed your iPad? touchscreen notebook? has a mirrored display of your camera. Would love to learn what software you're using for that 🤔

[architgarg]

Loved this video😇,
I am excited to share my GitHub as well.

[johnginos]

What do you recommend doing for a review of the interpretability of project outcomes. Let’s say I’m working on an econometrics project on my own, what’s the best place or way to review that I’m drawing the correct conclusions from my results? A lot of data science online sources simply take you through the code and the outputs but don’t go into how to make sure you’re drawing all conclusions from the model.

[checkingari]

Another nice video.

Ken, I have a question here. Which one is better, do we have to put one project in one repository or do we put several projects in one repository? For instance, this repository is a repository for the projects that I have done by taking a dataset from Kaggle.

Thank you Ken

[iskandarzulkarnain]

i am on my way to doing my first project and i hope you can review my portfolio then

[dheerajkumark]

Helo sir, I am DHEERAJ KUMAR I have mailed you my GitHub link and Portfolio last month, kindly request you to review it sir