I just want to say thank you to all the Deep Learning AI staff and community who taught me everything I know so far about Machine Learning / Deep Learning. I started my bachelor’s thesis about 7 months ago, when I submitted it, the university told me we could publish it as well.
I am 100% self-taught from these courses and various books and after all this time, I managed to do a good enough project! So once again, thank you 
Here’s the pre-print as the paper is still under peer-review:
Congratulations @Marios_Constantinou !!! I started to read your paper. I wish you great success! Hopefully your work, this one and the future ones, benefit humanity, as is the goal and orientation of our dear Prof. Andrew Ng.
@Juan_Olano Thank you! If you have any feedback, good and bad, I would gladly take it so I can improve on it
I am not an expert at all, just a student, so my judgment is limited. However, having read your paper, I find it very clear, very structured, and most of all, I can see how thorough you were in the execution of all the steps - a great example of MLOps!
Very interesting results.
Hi Marios. I did a very quick read of your paper and I find it very interesting and well written. I guess you could send it to a journal as it is now (there probably will be some comments from reviewers asking to improve or clarify things, but that happens always). If you want to improve it, maybe this could help:
1- Try to use less tables and figures in the results. I see you use one metrics table and one confusion matrix for each model. It would probably be more interesting to just expand the last table that compares all the different models.
2- The discussion section could be improved by making more specific (and of course, always respectful) comparisons to the results shown in other studies.
3- I see a few strange word choices. The message can be clearly understood, but maybe you can double-check with a native English speaker.
Thank you for your feedback. I do agree that there’s a lot of tables that could be merged into one and the discussion section does need some work as well.
Kudos to you. This is really good…
It’s published!
Congratulations @Marios_Constantinou on completing your bachelor’s thesis and having it accepted for publication! That is a significant accomplishment and a testament to your hard work and dedication.
I am thrilled to hear that our community and courses were able to play a role in your learning journey and helped you to achieve this success. It’s always gratifying to hear that our efforts are making a positive impact on people’s lives.
I hope you continue to find success in your future endeavors and look forward to hearing more about your work in the field of machine learning and deep learning.
Thank you for your kind words. The courses of deep learning ai did not just play a role in my learning journey; they were the key of my “success” since I am self-taught.
After my publication I also got a job offer as a research engineer on computer vision which I start in a week! Exciting things are happening and I can’t wait to see what’s next!
I wish I could personally thank Andrew and all the team / mentors / professors who worked on these courses, making machine learning more accesible to people like me!
Wow, congratulations @Marios_Constantinou on getting a job as a research engineer in computer vision! That is a huge accomplishment, and I’m so happy to hear that you’re making progress in your career.
I’m glad to hear that our community and courses played a key role in your success. Self-teaching is not easy, but you have demonstrated that it is possible with the right resources and determination. I completely agree with you, the courses in DeepLearning.AI are really great and make machine learning more accessible to people like you.
I wish you all the best in your new role as a research engineer and can’t wait to hear about all the exciting things you will be working on!