These books will help you learn machine learning 

Did I miss any? What are your favourite data science and machine learning books?

Cheers to Daniel, Keep leading.... and finding the best resources for you (and us). Learning happens different for everyone but you help show how to gut it out.... and get substantial amount learned in a short period on you path to success.

What draws me to your channel is your Honesty!! You never exaggerate the things. Nice video AS ALWAYS

Greatly appreciate you sharing your reading list, so to speak... Thank you so much for that

Excellent video! Thanks so much for the clear and concise reviews as well as the links. Very helpful!

I saw this channel at 5k subs and in a month it has crossed 12K, so cool!!!

Great list. Thanks Daniel !!

Daniel you are awesome and very generous in sharing the knowledge...the love the way you explain the things...great..

Thanks a lot for reviewing these books.

Nice list! I have DL and the 100 page book from this list. Love those two specifically for the reason they dont have code. I have a few coding books but the risk or problem there is the code will change as you correctly pointed out. The next level after DL are some phd level math books 50% written with greek symbols lol

i dont often comment but your work is really good n must appreciate!!! Thank you for helping fellow like me :)

thanks a lot for sharing those great books

Awesome and thanks for the video

Thanks for the links!

I can really recommend Trask's book. Will continue reading it while travelling :D

I Want to start machine with all vigir but I didn't knowwhich books to use.. Thank you soo much for the insights

Great content, thanks Daniel.

Time to buy Physical copy of Deep learning(Ian Goodfellow) Book, since I was reading it online for the most time. Amazing Video Daniel with great content as Always Brother.

Bro , plz make a machine learning course. You read so many books and worked in industdy.

great stuff man thank you

Thanks broo, Great work!

Thanks for the inspiration

Thank you Daniel !!

Very nice video, few statements are well said. Turns out that scikit tensorflow O'Reilly book is very highly rated amongst the community

Excellent review

I would like to recommend "Pattern recognition and machine learning" by Christopher Bishop and "Understanding Machine learning" by Shai Shalev both for the Mathematical issues involved in research algorithms and more

Nice video. Here are some other books that are worth reading/studying. 1) Elements of statistical learning (if you have an advanced math background) or Introduction to Statistical Learning by Tibishirani et al. 2) Machine learning: A probabilistic perspective by Kevin Murphy [I am not a die hard fan of this book but it works well for most cases] 3) The book of why-Judea Pearl (An amazing "semi" technical book that talks about causal inference; a critical piece that's missing in machine learning and deep learning)

Daniel awesome video again Good one buoy 👍

guys wait for the 2nd edition of hands on ML, its right around the corner

Currently reading Elements of Statistical Learning to get the math foundation. Truly recommend

Great list! Thank you for sharing. I would like to recommend "Python Machine Learning - Second Edition" by Sebastian Raschka and Vahid Mirjalili. This books really achieves a nice balance between practical implementation of ML models using SKLearn and the gory algorithmic/mathematical details.

Hey Daniel, awesome content as always. I'm stuck after finishing the Deep learning specialization course. What should I do next? Do you have any project or course recommendations?

How do you feel about using a kindle to read some of these books considering they can be graphic and color and text intensive?

Reading is learning. You are correct about that.

Wow, what a great guide! The Hundred Page Machine Learning Book is indeed extremely good, especially for intuitions. As a CS undergrad, I was trying to use The Elements of Statistical Modeling (recommended by my professor), which is insanely hard to understand xD Anyway, thanks Daniel! You definitely deserve a lot more subscribers:)

thanks

Great recommendation.Would like to also get some tips on developing GRIT to Get through ML Journey

Please make a updated vid on same topic , thanks

thank you for good books, any tutorial or demo videos? or maybe favorite websites for data science beginner

Grokking Deep Learning - best book! does not use popular frameworks and libraries this is a wonderful book. if you know the same then tell me. Andrew Trask great teacher

Am a beginner in this field and your video is so helpful for me now so i would like to ask you which book should I read first and so on until the last one?

Machine learning for humans is really good I'd highly recommend this ...

Great video again

Great video thanks for sharing! Recently got a few of these books myself :)

Hi Daniel, can you please make a video that tell us about your desk? I see that the brand is varidesk.com, but I don't know which model. Thanks

I have "Python for Data Analysis" and "Hands-on Machine Learning with Scikit-Learn and TensorFlow". Other book I recommend also "Python Data Science Hanbook" the author is Jake VanderPlas.

thanks for the video, can you suggest some books for deployment of machine learning model?? i am building a portfolio and i need to learn model deployment. thanks :)

My university used Artificial Intelligence: A Modern Approach as textbook, so i believe that this book is good enough

9:20 "You should be reading at all times a book that is slightly too hard for you to read." 😊 Well said. I like discovering books on my own but I also like hearing about the books other people find useful. Thank you for sharing your recommendations. I've only read two of these books so far. Have you read "Mastering Feature Engineering" by Alice Zheng? Do you have any recommendations on books about feature engineering?

Hello Daniel. If you had to choose between these books or udacity and coursera courses which would you choose?

Hands on machine learning is my fav

I expected Introduction to Statistical Learning but still a great list!

Hey, I was wandering for buying a GPU. I have some question that what sort of the GPU provider (MSI, ASUS, Gigabyte, EVGA, Zotac) is best suited for the ML model training. I have an MSI RX 570 card. How'll I set up my station for training?

Hi, I do love your books. I am totally beginner and now working on medical data ("big" data). Could you introduce me some books that fit to me?

Hey Daniel, Do you have the second edition or first edition for Python for Data Analysis? Thanks

Knowledge is power

How much time is needed to learn machine learning or deep learning from scratch?

Which one is the perfect book for someone who has just started learning ML. Which clears the basic! Thx

Excuse me bro would u like to tell me about the pc configuartion for ml or ai please i want to build a pc for ml ,ai focusing

Thanks for the recommendation on Trask's grokking DL book, I'm having fun with it (most of the others I already have :) )

Introduction to machine learning with python? Is it good book?

Recommend some books regarding math for ml, data science

Hey Daniel. Do you remember me asking you 4 or 5 months ago that I've started a new course on machine learning basics with python? Well, I finished it and got my certificate. I participated in some kaggles competition (ranked at top 35% in the houses prices). But I am stuck now. I don't know where to continue and what should I do next and what to learn to advance in this field. Can you advice me?

Remake the video with new list of book?

no wonder why his voice sounds familiar. I am doing his course on Udemy and its worth it. So good explanation.

Any recommended book on ML/DL with FPGA implementation?

Hi, can you recommend a deep learning book for beginners?

Is there any book that's akin to The Hundred-Page Machine Learning Book, but more on the topic of Data Science?

It's not about what ml is now, it's what they can become. DL bring the most likely culprit in my mind. I know dl is ml, but dl seems like the most likely culprit

I have just finished python machine learning third edition. What should I read next.

Do you need to know "general" Python before going into machine learning?

Is this book for beginners?

Hey Daniel, how did you get started with coding/maachine learning? college or self taught? Your videos are awesome!

I think that An Introduction To Statistical Learning is a great piece. Great for starters.

Hi guy, I have a question. I am about to write a research paper with machine learning , but I am not so good at Math. Is it okay just to use machine learning approaches like SVM, KNN, Random forest..... ? Without good understanding of Math, it’s hard for me to create a model . I’m new to machine learning , guide me if I misunderstand about this? Thank you in advance.

Grokking Machine Learning by Luis G. Serrano

Quick question: Is it possible to go deep into ml/ai without python? perhaps java and c++ are suitable too? Thanks for the vid regards from Greece

are freecodecamp certifications worth it, for the new python courses that are out there?

Nicep

Wow!, you also got the sleep tracking ring with Siraj; great video, I think I will get the Python for Data Analysis.

Sir, How can i start machine learning??? What are the things is necessary to start step by step..???? Thanks in advance

What's your Github? We can code review your code.

Your books are in new condition, did you read it?

Its 2023....Is it worth reading these books? Please give me some suggestions..... I'm a complete beginner and don't know how\where to start.....😔

Deep learning Yoshua Bengio, Aaaron Courville and Ian Goodfellow is a book for those who master all concepts of deep learning and have strong mathematical background (at least 2nd year of college math class) , and i don't recommend it if you want to start deep learning because it is for expert and it will threaten you 😄

Of course people are different, and it's a matter of personal taste, but here's my unsurpassed Top 3 (in order of LEARNING, not the quality): 1. "Mathematics for Machine Learning" by Marc Peter Diesenroth, A. Aldo Faisal and Cheng Soon Ong, Cambridge University Press, 2019. This has ALL the math you will need (except for the deep learning algorithms alas), in the best possible form, and NOTHING you won't need. You will really master PCA and SVM after defeating this book. Every chapter has a lot of exercises, and, believe me, even if you consider the chapter totally clear, you aren't going to do these exercises easily! 2. "Fundamentals of Machine Learning for Predictive Data Analysis" by John D. Kelleher, Brian Mac Namee and Aoife D'Arcy, The MIT Press 2015. This book not just explains the basic ML methods to you, it really shows the right METODOLOGY, which is extremely important. It represents everything you need to know about the basic non-deep methods (regression, classification and clustering), including some theory and the detailed explanations. My DS course was too hasty, and I didn't even realize that I don't have to encode categorical variables for Decision Trees and Random Forest until I read this book! 3. "Hands-On Machine Learning with Scikit-Learn, Keras and Tensorflow" by Aurelien Geron. Grab only the 2nd edition, it describes Tensorflow 2.0! Awesome book. Simply awesome. We have used it in our course for Deep Learning, and it describes them all: ANNs, CNNs, RNNs, even encoder-decoder and many others. All with good and working examples. Of course, "Deep Learning" by Ian Goodfellow and others is a great book, but I feel it's too academic. I guess nearly half of the material you will never need, but who knows? I will take it after I will know the Top 3 extremely well. "One-hundred page book" is a great reference once you already know all the details, but not earlier. And while I am very grateful for Wes McKinley for Pandas, I still prefer Theodore Petrou's "Pandas Cookbook", since it has everything I need, well-described and with good examples.

Good, love from Ukraine

Hey Daniel, if you don’t mind, can I send an email and ask you for some information about a career in DS and ml and how the job situation in Australia is

Those who will study ML at university will likely also use Machine Learning - Mitchell =)

None of them are available in India.

I have been subscripted your channel. thanks for all the books your advice.

Ray Gillette doppelganger! XD

7:13 HAHAHAHAHHA 🤣🤣🤣🤣🤣🤣🤣

Hello sir .. iam applying phd can I have your email please ? .. I want asking you about my topic thesis

The way you speak sometimes feel like Billy from strengerthings , or are u Australian..?

nt

Hands on Machine Learning is outdated as hell. Codes for Tensorflow will not work, a new version of this book is about to be released for Tensorflow 2.0 which will also include a few bits of Keras and it has Francois Cholette as a co-author.

please can you put your email here

Good video up to one point: I think "no, I've read this book and know what machine learning actually is" is the wrong answer to "are robots going to take over the world". Not only is "no", which implies a 100% certainty and is absolute in value, wrong in way too many cases (including this one) and "I've read this book and know.." sounds more like religion than science, but the question itself also didn't ask "with current ML techniques" or mentioned any restriction for that matter - the question was way too broad for a simple "no, I know it" answer. The right answer should be way longer and shouldn't include a clear "no" at all, at best a "if, then not yet or anytime soon". Just because you can't model an AGI with current machine learning algorithms , or any Artificial Intelligence approach for that matter, doesn't mean it won't ever happen. If a "close to human intelligence brain" is nothing but the sum of it's parts, then it will be artificially created one day, at which point robots would indeed be capable of taking over - unless the AGI was designed properly. Which is hard as we don't even know how to define that "properly" yet. So Instead of saying "no" I would've rather returned a question and asked about the time horizon of the question. I know it was supposed to be an example (and a joke about the apparent fear about AI I guess), but I think it wasn't a good one.

The Element of statistical learning gang ?