I've got a new favourite machine learning book | Machine Learning Monthly October 2020

[@blacklabelmansociety]

I contributed to the ML Engineering Book. My name is somewhere inside it. I’m really glad you enjoyed the content and I somehow gave something back to you, Daniel!

[@mrdbourke]

Woah! Thank you for your efforts Alexandre, I loved the book!

[@spaceyfounder5040]

My brain is blown by that amount of information... that way I'd never focus on one project, one goal. BTW awesome job man, you've got a new subscriber :D

[@KenJee_ds]

Love the shirt!!!

[@arianrahman4840]

Love it when two of my favorite channels cross over

[@mrdbourke]

Thanks brother!

[@paragjadhav4735]

@@arianrahman4840 me too brother

[@shatandv]

Daniel, thank you so much for this. I've been enjoying your content thoroughly and it helped me understand Data Science and specifically ML a lot better. Your positive energy really inspires me to go ahead and create something myself. I hope you're enjoying doing this KZbin thing too.

[@mrdbourke]

Thank you so much Shatandv! That's a massive compliment. Keep creating my friend, plenty more videos to come

[@pabloarvilla8012]

Getting use to these long videos, a lot of interesting points you made. Keep the good work, definitively one of my favourite channels for ML!

[@mrdbourke]

Thank you Pablo! I really appreciate it

[@kasozivincent107]

Daniel i really liked your machine learning roadmap. That’s why I smashed the like button and subscribed. I love your content

[@mrdbourke]

Thank you so much! Plenty more videos to come

[@kasozivincent107]

Hey Mr. Daniel. I am an upper computer science undergraduate. I am planning to do my final project in Machine Learning. What kind of cool project could you suggest for me?? Thank you. May you help me with your Twitter account?

[@bhaskar0903]

cool shirt.. after working for around 14 years after my college , watching these videos got me hooked into books and start appearing for exams.. learning shall not stop and books are really one's best friend. also keeps you young ;-)

[@mrdbourke]

thank you thank you thank you! So stoked to hear you're loving the learning journey my friend, all the best for your exams!

[@kotiswarooptadepalli6299]

Perfect guidance for my ML self study journey. Thanks Daniel

[@mrdbourke]

All the best Kotiswaroop! Thank you for the kind words

[@fatemehcheginisalzmann2189]

Daniel, I really enjoy any minute of your videos that are informative and helpful. Thanks a lot!!!

[@mrdbourke]

Thank you Fatemah! I really appreciate it!

[@theloniousMac]

Commandment number 1 used to be known as “Garbage in, garbage out” or “gigo” in computer science.

[@mrdbourke]

Great heuristic

[@07749044102joe]

Thank you so much for all your videos. It is fantastic to have someone layout all the great resourses on machine learing in one place. Unbelivably great space for someone who is trying to get into machine learing and wanting to better themselves constantly in the field. Keep it up!!!!

[@mrdbourke]

Thank you thank you thank you! Plenty more videos to come :)

[@ChaiTimeDataScience]

Been Loving the ML Monthly series! We need a new fitness newsletter too :D

[@mrdbourke]

You’re right! I’ve got some ideas cooking on the fitness front

[@ChaiTimeDataScience]

@@mrdbourke Can't wait! :D

[@FarisSkt]

Please keep uploading, you’re awesome

[@mrdbourke]

Plenty more to come!

[@RJ-stills]

Your channel is Epitome of Best Self Dev+ML content!

[@mrdbourke]

That’s a massive compliment, thank you RJ

[@theloniousMac]

Odd little things. I’ve heard the word evergreen must be zillions of times and it only just now, because of the way you used it, did it occur to me what it meant, but then thinking about it, maybe I haven’t heard the word used very much... in America. Interesting.

[@rishisaireddysudireddy5437]

Thanks for inspiring. I’m becoming a productivity machine! .

[@mrdbourke]

Keep getting after it Rishi!

[@dimka1699]

That is pretty interesting to know about your monthly articles about actual things in Mashing Learning! Thank you, Daniel🙏🏼

[@mrdbourke]

Stoked you enjoyed Dmitriy, thank you for the kind words

[@engrgit]

Awesome Daniel. I find the resources quite useful. Thanks for doing this.

[@mrdbourke]

Thank you so much, plenty more to come

[@ashishbhatnagar9590]

Very nice video Daniel. Thank you so much for these videos. They are very informative and helpful.

[@mrdbourke]

thank you Ashish! So stoked you enjoyed

[@egehurturk6209]

I also got this book! Love that!

[@mrdbourke]

Phenomenal book

[@vincebartle]

22:30 you could read down and sit it in one day or you could down read and day it in one sit; it's personal preference tbh

[@amirkhalesi5294]

Great work as always Daniel. Keep up the good work!

[@mrdbourke]

thank you Amir! I really appreciate it

[@kirtipandya4618]

You said that book is in your top five books. What are other four? Thank you in advance. 🙏🏼

[@mrdbourke]

(no order) 100 Page ML Book Machine Learning Engineering Hands-on Machine Learning with Scikit-Learn and TensorFlow 2.0 Mathematics for Machine Learning + a wild card! (Undecided here)

[@krishmoore]

Hi can you give me the link for the book "Machine Learning Engineering by Andriy Burkov" to read ? Thanks

[@mrdbourke]

You've got to try harder! It's the first link on Google: www.mlebook.com/wiki/doku.php

[@andynguyen4719]

Great video as always Daniel! May I ask what monitors are you using?

[@mrdbourke]

Thank you Nd! I'm using a LG UltraFine 4k (24-inch) + a Dell 27-inch but I think the 27-inch is a little too big

[@hlomphomota8055]

Your videos are amassing. Hope to meet you at some point in life.

[@mrdbourke]

Thank you Hlompho! Glad you’re enjoying them

[@harisumanth]

Great video! Would love to see future videos in 16:9 or hopefully 18:9🔥

[@mrdbourke]

What happened? Not sure if it got recorded correctly 🤔

[@jonathanvevance1963]

Love your videos! Thanks.

[@mrdbourke]

Thank you Jonathan! I appreciate it!

[@Duge6124]

I’m trying to decide on buying between a MacBook Air and MacBook Pro (the M1 architecture) which one is best suited for ML. Which specs are the most important if you want to be future proof in the field

[@mrdbourke]

currently writing this on a MacBook Air, it's great. You can write ML code on any laptop, however, it's probably not wise to train large deep learning models on any MacBook. M1 architecture is still fairly new so there will probably be some time before it's fully integrated with many ML frameworks. Though TensorFlow seems to be coming across: blog.tensorflow.org/2020/11/accelerating-tensorflow-performance-on-mac.html I've ordered a MacBook Pro with M1 and am going to test them for ML tasks. The setup I currently run: write code on MacBook Pro (16-inch), execute it on Google Colab/Google Cloud for GPU (deep learning models).

[@user-to7dp2uc3o]

Very nice video

[@mrdbourke]

Thank you 🙏

[@glorialinda3038]

Hello Daniel, which default search engine do you use? Thanks!

[@mrdbourke]

Google/DuckDuckGo

[@premkamban]

Hi Daniel, if am preparing for FAANG for machine learning engineer , data scientist or applied scientist positions then what is the process I can follow : Currently working on machine learning roadmap 2020 (share by you), the question is either I can start system design first or data structures first else what percentage of coverage I can go for, because i have to cover a lot in machine learning side . Note: I have planned to prepare for 6 months from now! Please advise me on this. Request: Please add this topic in your upcoming video , hope it will be useful to all.

[@mrdbourke]

Hey Prem, I’ve never been a machine learning engineer at FAANG so I’m probably not the best person to answer this question. I’d research some of their machine learning engineer job roles and see what they list as requirements, then get in contact with people who work in those roles to see what it’s like.

[@premkamban]

@@mrdbourke thank for the response!!

[@nimaazbijari665]

Awesome stuff!

[@mrdbourke]

Thank you Nima :)

[@polimeracharikshith5025]

i love your videos . it has been very helpful. Keeping doing it. Do u have any idea of pytorch . i have issues with "import" importing custom functions . Could you help me out please.

[@mrdbourke]

Thank you Polimera! Glad you're enjoying them. As for PyTorch custom functions, I'm not the best person to help out there

[@vinigunner94]

Legend ! thanks for the video. I was wondering how valuable do you consider books when compared to online resources. For example A great python book vs DataCamp or CodeAcademy ? Sometimes I wonder if books are the way to go, but these online resources also have their place right ? What do you recommend ? Cheers mate, appreciate your content.

[@mrdbourke]

Yo! Glad you enjoyed the video. I personally found online courses to be best for beginners but once you've got some experience, you start turning more to books/documentation. I always recommend trying something and if it works for you, use it, if not, move on.

[@vinigunner94]

@@mrdbourke Brilliant mate cheers, I sent you an email btw

[@ashishk81]

Hi Daniel , Thanks for "A 2020 guide to Data & Infrastructure " , i am machine learning engineer working from last 3 years , wanted to move into Data Engineering career path . Surprisingly i didnt find single end to end free online resource to start my journey in Data Engineering . If you know any free(or paid) and very demanding resources , please reply to this message i have been following from last 1.5 years and it really help me shape my career .. thanks

[@mrdbourke]

Yo Ashish! Thank you for the kind words. As for data engineering, because there are so many options, the best resource would be to build your own data-powered app and learn the principles and skills along the way

[@akashtriz]

You need to be your biggest fan, let's be real👍🎉👍😎 #SoDangTrue

[@rzwnhmd]

hi, do you use roadmap creating tools (not whimsical but something that has a timeline for completing tasks). if yes can you recommend me a good one. A free tool would be much appreciated ;)

[@mrdbourke]

I love Trello/Notion, I've used both extensively. Now I mainly use a text edit document

[@kolla_teja]

i want to know about transformers. can you suggest me some ways to know what it is.

[@mrdbourke]

I’d start with the paper “Attention is all you need” and then lookup the post “transformers explained”

[@kolla_teja]

@@mrdbourke thanks bourke

[@rachelbartley6540]

Hello Daniel, I am a high school math teacher that has recently (within the past 2 and a half months) become interested in Machine Learning. I have been working on learning Python and the various libraries that are necessary for ML, big thanks to you for giving me a guide to follow! I am interested on using Machine Learning to create personalized education. Are there any resources you could recommend to help me specialize on machine learning for education? Are there also any contacts you could give me for people/companies who are interested in the is topic? Thanks so much!

[@mrdbourke]

Hey Rachel! That's so exciting. My favourite ML products/creations are seeing someone with a background in something else coming to the ML field and figuring out how ML can help their field! As for education, I'd checkout Korbit, it looks like they use a form of machine learning to help people learning data science, may be worth getting in touch with someone there? www.korbit.ai/ Otherwise, I'd keep going the way you're going, one of the challenges of ML is being able to formulate the problem you're trying to solve (and whether or not ML is the right tool). So I'd have a think about the problems you face most often in the education space and start to try and formulate them in terms of an ML problem.

[@rachelbartley6540]

@@mrdbourke Thank you! I was checking out Korbit.ai today and it looks very intriguing. Also just bought my own: Hands on Machine Learning book and am excited to start working through it!

[@rachelbartley6540]

Also, one more question, after going through the State of AI Report 2020, would you recommend learning Pytorch or Tensorflow? Or both?

[@mrdbourke]

One of my favourite books ever, I read some of it this morning

[@mrdbourke]

Both are phenomenal. I have more experience with TensorFlow though. You can do basically the same thing in both frameworks. If you’ve got hands on ML, it’s pure TensorFlow so I’d stick with that. However, PyTorch books/resources are also a plenty. Best to choose one and stick with it, if you get good at it, bridging to the other won’t be too difficult.

[@vikramc.n.1121]

hi sir, thanks for the video, cool shirt by the way

[@mrdbourke]

Thank you Vikram! I really appreciate it

[@varunkumarsharma1797]

Very nice shirt broo

[@mrdbourke]

Thank you Varun!

[@abdullahziker]

Daniyel you gotta watch comma ai archive coz george hotz just wrote tiny grad😳😳😳😳😳any comments on that??????😳

[@mrdbourke]

Looks amazing! I love watching George Hotz code

Handsome 😍 dude

[@mrdbourke]

😙