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John Enad
John Enad

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Day 33-37: Joined Kaggle community

In today's post, I want to share a brief update on learnings. As I mentioned at the end of my previous post, I was thinking about joining kaggle.com.

For those who might not be familiar with Kaggle, it is an online community that offers a wealth of resources for learning about Machine Learning and Data Science. The platform welcomes users of all skill levels, from complete beginners with no programming background to expert Data Scientists and Machine Learning Engineers. Kaggle has tens of thousands of public notebooks and thousands of public datasets, providing lots of opportunities for hands-on learning.

Kaggle also offers free courses aimed at helping aspiring Data Scientists build their skills. Also, the platform hosts online competitions that challenge participants to push their learning even further and put their knowledge to the test.

Since joining Kaggle, I have completed three free courses and received online certificates for each:

The first two just served as a review for the Python concepts I've learned the past few weeks but the basics of Machine Learning was something entirely new. I'm excited to continue exploring Kaggle's offerings, as I believe it is an invaluable resource for anyone looking to break into the world of Machine Learning and Data Science or at least to understand what it is.

Since I have just started and have only been focusing on the free courses, I have yet to experience the online community aspect of Kaggle. It is supposed to provide a sense of collaboration and allows users to learn from one another. Hopefully, this supportive environment would help accelerate my personal growth and development in area.

In summary, if you're considering going into Machine Learning and Data Science, Kaggle is a wonderful place to start. With its extensive range of resources, courses, and competitions, the platform offers lots of opportunities for learning and growth.

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