Master ML Papers without Losing Your Sh*t

Tired of struggling your way through Machine Learning research papers?

Latest deep learning models got you feeling down?

Ripping out your hair trying to stack layers?

Losing the plot over…plotting loss?

I hear you. Let’s face it, reading Machine Learning and Deep Learning research papers can be tough. Having a process to systematically break them down makes working through them a whole heap easier. In this video you’ll learn how to do exactly that.

Links Mentioned

Chapters
0:00 - Introduction
0:39 - 1. Take a Breath
1:28 - 2. Read the Abstract, Conclusion, Data and Results Section
3:43 - 3. Get the Code
5:29 - 4. Isolate How it Was Built
9:49 - 5. Try it Out Yourself
11:36 - Ending

Oh, and don't forget to connect with me!

Happy coding!
Nick

P.s. Let me know how you go and drop a comment if you need a hand!

[Saritm]

Thanks, Professor Renotte. Your effective but simple thinking astounds me.

[OopsCoca]

thank you, Nicholas! U just saved me from the pain of reading deep learning papers. Pls keep going on your AMAZING jobs.

[muditrustagi]

this was a much needed video, thanks Nick!!

[strategy_gal]

Great tips, Nicholas! Love how you broke down the steps and clearly explained how to do it.

[marciovalverde]

OMG, it´s awsome ! will help me a lot with my researchs ! Thank you so much !!!!

[weekendwargamers]

100% increase my level on reading ML papers 🧙🏼‍♂️

[sharankalyan]

Wonderful video❤️. Will definitely try and follow 👍🏻

[akankshasinha]

Thank you so much for the insights & tips on mastering ML Paper! I love your workstation setup, can you please share the details about your setup dual screen, camera, table, laptop, etc.

[vikashchand.]

Yo! This video was a NEED!

I recently tried reading an ML paper but I found myself lost half way in 🤦‍♂️😂

Thanks! 🤘🔥

[ameerazam]

Again best ever …. It’s really amazing seems to be same as before coding more focus on theory ….cheers ….

[ronaktawde]

hey man... I have become big fan of yours. great video!!

[lucasmadrassi]

Hi Nick. Have any ideas about AI for actually papers?

[alifiyabatterywala]

please do a video on ML papers recommended for beginners

[NarutoUzumaki-lqyk]

@Nicholas, scikit-learn more useful than tensorflow or

Scikit-learn is better for ML and tensorflow for DL?

[Burakyesilvlogs]

Can you also make a video on how to fine tune Bert to make model like keybert for keyword extraction?

[mikecooper]

speaking of facenet paper, please make a video about triplet loss/siamese net/one shot learning!

[atanujana]

Sir pls create a video on mask detector using react js

[prakhars]

would you like to explore physics-informed machine learning in your future videos? For example, physics informed neural networks PINN, data assimilation or system identification. I am saying this because you won't find many videos on PINNs on Youtube.

[microgamawave]

Please make a video about facial recognition in Python🙏

[markusbuchholz]

Thanks Nicholas for your recommendation. You are doing impressive and outstanding job! I do believe that your great community will be also impressed and apply your recommendations accordingly. We are very lucky the "paperwithcode" has been launched. All the papers are impressive but I do believe with quantum computers which probably will change a bit the "concept" of ML, AI and DL. We know you work in IBM and I think it will be awesome if your future videos will depict some ML project based on Qiskit. IBM makes remarkable work in quantum computer technology and probably it will be great also to approach this concept to others. IBM website is a rich source of information (outstanding) . Thank you for your effort. Have a nice day!