Regarding why it's free, when I worked for state government in the U.S., I was told that, if the University received Federal money for the project (software, textbook, online course, etc.), the University could not charge for it. This is why you can get some marvelous things for free if you know where to look. I recently downloaded an MIT graduate school textbook on complexity theory for free.
I first saw this video a couple months ago, picked up the recommended "make it stick" book, and just finished it. I can attest that Giles is doing a great service by recommending this book. I agree that it's essential reading for anyone serious about learning and optimizing the learning process. Thank you sir!
I have read the book last year during my university course focused on machine learning. It gives a pretty good understanding for machine learning. But to become a data scientist you need Python or R, SQL and shell scripting and most important: practical experience in those languages. Even the best book doesn't help if you don't apply the knowledge.
Domain knowledge is key to a given career area, for sure. But when I'm reading resumes, I do enjoy finding someone who knows all three (R, SQL, and bash). Though I can teach the latter two on the job if needed.@@FsimulatorX
@Jeff-ih4rk data science is often depicted using a venn diagram showing the intersection of computer science, statistics and domain expertise. Domain expertise is the knowledge in the field you are doing data science in. If you are analyzing business data for a large online shoe producer, your domain knowledge is economics and shoes (and maybe online marketing). If you are analyzing climate data, climate research is your domain expertise, etc.
In my case, i forgot all the heavy math staff from the book after 6-8 month. Ofcourse, there are general familiriaty with all the concepts and models, but if you not digging it deeply everyday, its just vanishes. Maby it's the way to go if you are not working in academia, research or inventing new data algorithms. Or maby its just my brain throw it away, since most time its about data cleaning and tuning scikit-learn models( i am just a hobbiest doing it for fun, not a professional in the field)
Excellent! Glad to see it come out in Python. When I went through the 2nd edition, I just forced myself to learn it both R and then translate it into Python because there wasn't an option.
This is the recommended book for the Society of Actuaries Statistics for Risk Modeling Exam- along with the book Regression Modeling with Actuarial and Financial Applications, by Edward W. Frees, 2010 for their data science micro-credential.
I just stumbled onto your channel and in 1:50 I love your thought process. ISLR was the BEST book for data science, focusing on R, that I was assigned while earning my MS in advanced data analytics. Making It Stick, was the BEST book I read to help become a better teacher. I often thought it should be required learing for ALL teachers and learners.
I read half of this book last year, It probably is the best book out there to study machine learning from ground up and build intuition for it, Fun Fact, one of the authors of this this book(Daniela Witten) is the daughter of Edward Witten(the physicist) iykyk
Regarding Stanford I'd like to add a great experience I had with free classes some time ago using Java. These were recorded sessions and a course outline and links to source. I was searching around for a refresher on Java because I got a book on Mobile app development with Native Android. The book was using Java at the time (these days it is Kotlin for Android). We built a number of applications and it was a lot of fun. Could not believe they offered this for free and there was a substantial amount covered.
People thinking that they're going to be able to leverage the info in those books without the necessary maths skills to do so are going to be sorely disappointed.
Yep, it should have been mentioned in the very beginning of the video. Data Science is a Science and based on high math. From linear algebra to statistics and calculus.
ESLR and ISLR are one of the best statistical learning books out there. Read both of them during Data Science and Data Mining classes in grad school and I still go back to them!
Agreed! I read ISL during a beach vacation years ago when I was learning data science. I still turn to ESL for reminding myself of the intricacies of a given algorithm.
@@Dionysus-01 elements of statistical learning. Profs Tibshirani and Hastie’s original stats book. ISLR is an easy to understand interpretation of ESL by their PhD students. Once you read ISL, ESL is the book to move up to for a deep dive on those concepts. Really heavy on the math yet intuitive.
YOU! Have such a great voice. It makes a person wait and listen to you. Really as a non subscriber, you just pulled me towards the video. Appreciate it.
I have that book on Audible and it is awesome. I recommend it to so many people and now realize I want to listen to it again. Changed my life- I just wish it had happened to me when I was 12. Great video, thanks.
This is the recommended book for the Society of Actuaries Statistics for Risk Modeling Exam- along with the book Regression Modeling with Actuarial and Financial Applications, by Edward W. Frees, 2010 for their data science micro-credential. Sorry, I forgot to add below that only the R programming version of the book is included in the exam syllabus.
Huge fan of brilliant. Have done the ISLR course. It is really good. I would recommend the MIT Micromasters in SDS after that. It is not free. But you get 90% financial assistance if you are eligible. Each course is 300$ each. There is a finance Micromasters too. Each course is 450$.
my question tho, if you're already "bad" at solo studying/self teaching and you're stuggling to maybe learn something specific, is it then still worth it to try learning the methods taught in 'Make it Stick'? Like does the book take into account the process of learning what its trying to teach? mostly silly question but I do want to get a copy of the book either way, its just that I have books that i felt would speed up my process of learning certain comp science topics, specifically the book 'Code' by charles petzold, but i cant bring myself to finish these sorts of books even knowing it would make learning everything related after the fact so much smoother.
I have both versions of this book (Python & R). I downloaded them to start with and then purchased hard-covered versions of both books. They are fantastic.
It depends upon the objective of the learner: whether to learn the theory and code by your own or to learn only to use ready made packages and get the result... For the second case, ESLR and ISLR (and the latest Python version) are really good as they did not delve into the nitty gritty of the theories... But for the first case, one should refer C M Bishop's PRML (2006) and Deep Learning by the same author and Kevin Murphy's ML- Probabilistic Perspective (2012, Edition 1) and latest in two volumes... PRML is freely available too in Microsoft's website.. In ESLR, ISLR I found the concepts are quite esoteric whereas in PRML and Murphy's book they have started at the basic concepts and slowly went on building upon the basics...
great transitions from frame to frame, it's a pleasure to watch. An example would be the way you introduce a stack of papers only to pick it up later thus creating a mini storyline.
I'm glad you've highlighted these excellent books. The statistical learning book has been around for a good number of years and is well-regarded by those who know it. I have read parts of it before and I've recently gone back to read it again after the Python version was published! :)
oh yeah, it's ISLP instead of ISLR. I have the latter and yeah, it's a great book! I worked through some, but I was completely lacking in a stats background of any kind, so I pivoted to learning statistics which has been great. I'm a big fan of R, but Python is a great (and more broadly applicable) language too. The R version is a bit dated now as there are more modern packages that are easier to use, but the fundamentals are all there and it's definitely a book worth having. I'm sure the Python version is excellent. The R version even has supplementary videos where the authors talk through topics. The name of the channel is datascienceanalytics.
@@paulfitzgerald4625 I bought a used statistics book on thrift books. I bought Probability & Statistical Inference by Hogg & Tanis. It's a good book, but it expects a couple of semesters of calculus from the reader. If you want a more standard "intro stats" text book, Statistics for Business and Economics from Cengage is much more accessible and requires a much more modest background in maths. It covers a very wide range of topics and statistics and is aimed at undergraduates.
Thanks for sharing this amazing resource! Stanford's free data science book and course are invaluable for learners. Can't wait to dive in and expand my knowledge. Great find!
So true!!! This book is absolutely top notch and while there are other great reources out there such as Oreilly and Coursera, this book provides all the prerequisite knowledge
I started Python about six months ago this ago. Before that DBA with extensive T-SQL programming experience. I tried that Stanford paper and I sure do not get the recommendation - way too complex and needlessly so for someone trying to learn the language. Python Institute’s intro books and testing worked for me
Best book on machine learning. Quick tip learn statistics first. Then learn mathematical statistics. The read a 100 page per month in 6 months you are ready . Then build projects
When I was going through a data science boot camp, in 2021, the instructor recommended ISLR. I tossed it to the side, because I don't know R. I'm glad that a Python version was released. I suspect that Python has surpassed R in usage in the data analysis realm.
I like Python, and its far easier to master than R, but I use R in my work far more often than I use Python. This may just be a bias among my management, but the fact that I knew R, and Matlab and Mathematica coming out of University made getting my first data analyst job much easier.
@@deusvult1268 I think in most instances Python is a more useful language to know. Python is now interoperable with Microsoft Excel which is used almost ubiquitously in data science.
This book is amazing! I have already read the R one, but this in Python has the potential to be the best out there! Thank you for sharing this with us.
Giles, thx for sharing that "Make it stick" book again. I just went ahead and bought it through you affiliate link. Should have done it the first time you recommended it. Better late than never.
As the other commenters have pointed out, the authors couldn't charge for it even if they wanted to, because this project was publicly funded. They're legally obliged to make it free.
Oh, I already have the book, but not the python version. Mine is in R. I am definitely uploading the python version ASAP. Also, brilliant isn’t free. Maybe they don’t charge much but definitely not free.
What should I offer for non-profit organizations? I assume they don’t know what data analysis can give them, and they probably don’t collect data.. Any suggestions? Thanks for the video!
Regarding why it's free, when I worked for state government in the U.S., I was told that, if the University received Federal money for the project (software, textbook, online course, etc.), the University could not charge for it. This is why you can get some marvelous things for free if you know where to look. I recently downloaded an MIT graduate school textbook on complexity theory for free.
Where should one look if you don't mind me asking? Also, do you have any other resources that you have come across that are amazing?
@@EngineerWallah same here!
It would be wonderful if the same logic were applied to pharmaceuticals and healthcare procedures
he is gone with no answers, and all books
thank you for your perspective, it is really valuable to know that!
The name of the book : An Introduction to Statistical Learning
It's in the links on video's description
This guy really made an entire video about a book without mentioning the book’s name lol
Lol😂
@@pepenavaodon't you have to buy it - looks like an Amazon link not a PDF link
@punkisinthedetails1470 No, you don't have to buy it
I first saw this video a couple months ago, picked up the recommended "make it stick" book, and just finished it. I can attest that Giles is doing a great service by recommending this book. I agree that it's essential reading for anyone serious about learning and optimizing the learning process. Thank you sir!
I have read the book last year during my university course focused on machine learning. It gives a pretty good understanding for machine learning. But to become a data scientist you need Python or R, SQL and shell scripting and most important: practical experience in those languages. Even the best book doesn't help if you don't apply the knowledge.
shell scripting? no you don't lol
Not necessarily at least. Domain knowledge is way more important
Domain knowledge is key to a given career area, for sure. But when I'm reading resumes, I do enjoy finding someone who knows all three (R, SQL, and bash). Though I can teach the latter two on the job if needed.@@FsimulatorX
@@FsimulatorX what is domain knowledge ? (is i'm a nerd, but want to hear your perspective
@Jeff-ih4rk data science is often depicted using a venn diagram showing the intersection of computer science, statistics and domain expertise. Domain expertise is the knowledge in the field you are doing data science in. If you are analyzing business data for a large online shoe producer, your domain knowledge is economics and shoes (and maybe online marketing). If you are analyzing climate data, climate research is your domain expertise, etc.
In my case, i forgot all the heavy math staff from the book after 6-8 month. Ofcourse, there are general familiriaty with all the concepts and models, but if you not digging it deeply everyday, its just vanishes. Maby it's the way to go if you are not working in academia, research or inventing new data algorithms. Or maby its just my brain throw it away, since most time its about data cleaning and tuning scikit-learn models( i am just a hobbiest doing it for fun, not a professional in the field)
Excellent! Glad to see it come out in Python. When I went through the 2nd edition, I just forced myself to learn it both R and then translate it into Python because there wasn't an option.
That book is meant as an prerequisite to their other book: Elements of Statistical Learning
I completed this coursework many years back when online courses just started.
Its wonderful. I created a basis for all my future work.
This is the recommended book for the Society of Actuaries Statistics for Risk Modeling Exam- along with the book Regression Modeling with Actuarial and Financial Applications, by Edward W. Frees, 2010 for their data science micro-credential.
Do you have a list/repository of all the books per subject recommended by SOA?
@@jackbluesman9223curious to know as well
I just stumbled onto your channel and in 1:50 I love your thought process.
ISLR was the BEST book for data science, focusing on R, that I was assigned while earning my MS in advanced data analytics.
Making It Stick, was the BEST book I read to help become a better teacher. I often thought it should be required learing for ALL teachers and learners.
That’s not the name of the book. If it was so integral to your life don’t you think you should know the actual title?
@@rogerc23, ISLR and ISLP are the SAME book, the former written for R, the latter Python.
@@rogerc23 Wise question. What is the name of the book, please?
@@GeorgesSegundo I was just being a dick and trying to be funny. The book is Make it Stick, not Making it Stick as he wrote above
I read half of this book last year, It probably is the best book out there to study machine learning from ground up and build intuition for it, Fun Fact, one of the authors of this this book(Daniela Witten) is the daughter of Edward Witten(the physicist) iykyk
I don't know what do you you mean iykyk?
@@idwtv534"If you know, you know"
@@idwtv534if you keep your kitten-by witten; get it he's rhymin & stillin...
Name
It was an absolutely beautiful surprise to see that ISL book has a version with R programing language examples!!! Thank God!!!
I used this book to study for the micromaster program of MIT. Glad to know that now we have a python version at last!
Regarding Stanford I'd like to add a great experience I had with free classes some time ago using Java. These were recorded sessions and a course outline and links to source. I was searching around for a refresher on Java because I got a book on Mobile app development with Native Android. The book was using Java at the time (these days it is Kotlin for Android). We built a number of applications and it was a lot of fun. Could not believe they offered this for free and there was a substantial amount covered.
People thinking that they're going to be able to leverage the info in those books without the necessary maths skills to do so are going to be sorely disappointed.
Yep, it should have been mentioned in the very beginning of the video. Data Science is a Science and based on high math. From linear algebra to statistics and calculus.
Which is better? This or the O'Reilly books for data science or statistics?
ESLR and ISLR are one of the best statistical learning books out there. Read both of them during Data Science and Data Mining classes in grad school and I still go back to them!
Agreed! I read ISL during a beach vacation years ago when I was learning data science. I still turn to ESL for reminding myself of the intricacies of a given algorithm.
@@LesserAndrew What's ESL?
@@Dionysus-01 elements of statistical learning. Profs Tibshirani and Hastie’s original stats book.
ISLR is an easy to understand interpretation of ESL by their PhD students. Once you read ISL, ESL is the book to move up to for a deep dive on those concepts. Really heavy on the math yet intuitive.
Elements of Statistical Learning(ESL)>Introduction to Statistical Learning(ISLR or ISLP)
Please mention the link to the free book.
YOU! Have such a great voice. It makes a person wait and listen to you. Really as a non subscriber, you just pulled me towards the video. Appreciate it.
I have that book on Audible and it is awesome. I recommend it to so many people and now realize I want to listen to it again. Changed my life- I just wish it had happened to me when I was 12. Great video, thanks.
THE NAME OF THE BOOK PLEASE ?
@@melyder2316 did you find out?
24% of this video is an ad. 😮
This is the recommended book for the Society of Actuaries Statistics for Risk Modeling Exam- along with the book Regression Modeling with Actuarial and Financial Applications, by Edward W. Frees, 2010 for their data science micro-credential. Sorry, I forgot to add below that only the R programming version of the book is included in the exam syllabus.
What else does someone need in order to become an actuary other than R?
Huge fan of brilliant. Have done the ISLR course. It is really good. I would recommend the MIT Micromasters in SDS after that. It is not free. But you get 90% financial assistance if you are eligible. Each course is 300$ each. There is a finance Micromasters too. Each course is 450$.
my question tho, if you're already "bad" at solo studying/self teaching and you're stuggling to maybe learn something specific, is it then still worth it to try learning the methods taught in 'Make it Stick'? Like does the book take into account the process of learning what its trying to teach? mostly silly question but I do want to get a copy of the book either way, its just that I have books that i felt would speed up my process of learning certain comp science topics, specifically the book 'Code' by charles petzold, but i cant bring myself to finish these sorts of books even knowing it would make learning everything related after the fact so much smoother.
where can i find the book?
I have both versions of this book (Python & R). I downloaded them to start with and then purchased hard-covered versions of both books. They are fantastic.
I have some questions about this book and courses. Would you please give me some of your precious time?
It depends upon the objective of the learner: whether to learn the theory and code by your own or to learn only to use ready made packages and get the result... For the second case, ESLR and ISLR (and the latest Python version) are really good as they did not delve into the nitty gritty of the theories... But for the first case, one should refer C M Bishop's PRML (2006) and Deep Learning by the same author and Kevin Murphy's ML- Probabilistic Perspective (2012, Edition 1) and latest in two volumes... PRML is freely available too in Microsoft's website.. In ESLR, ISLR I found the concepts are quite esoteric whereas in PRML and Murphy's book they have started at the basic concepts and slowly went on building upon the basics...
great transitions from frame to frame, it's a pleasure to watch. An example would be the way you introduce a stack of papers only to pick it up later thus creating a mini storyline.
I was looking forward to seeing a shot from under a table.
I'm glad you've highlighted these excellent books. The statistical learning book has been around for a good number of years and is well-regarded by those who know it.
I have read parts of it before and I've recently gone back to read it again after the Python version was published! :)
What is the Python version called?
@@seanmclaughlin7415An Introduction to Statistical Learning: with Applications in Python
oh yeah, it's ISLP instead of ISLR. I have the latter and yeah, it's a great book! I worked through some, but I was completely lacking in a stats background of any kind, so I pivoted to learning statistics which has been great. I'm a big fan of R, but Python is a great (and more broadly applicable) language too. The R version is a bit dated now as there are more modern packages that are easier to use, but the fundamentals are all there and it's definitely a book worth having. I'm sure the Python version is excellent. The R version even has supplementary videos where the authors talk through topics. The name of the channel is datascienceanalytics.
Me too. I quickly got lost. Where did you begin your statistics journey?
@@paulfitzgerald4625 I bought a used statistics book on thrift books. I bought Probability & Statistical Inference by Hogg & Tanis. It's a good book, but it expects a couple of semesters of calculus from the reader. If you want a more standard "intro stats" text book, Statistics for Business and Economics from Cengage is much more accessible and requires a much more modest background in maths. It covers a very wide range of topics and statistics and is aimed at undergraduates.
I love this book. I have the first one in hardback (the R version) and I’m considering buying the Python version too.
So weird... Among the *17* links in the description - I didn't find a clear link to the book itself.
Very professional.
Yeah. What a click bait video with no real useful content. Who cares why it is free if you can't even link it.
It's the third one: "An Introduction to Statistical Learning"
The title of the book is in the video.
PS: you should also put the links to the books in your descriptions.
i found the name of the book: An Introduction to Statistical Learning
he already did
And the for then edx course you have to google: An Introduction to Statistical Learning edx
Can anyone please hare the link for this book?
the video tutorial for python version will release on summer of 2024 on edx platform.
Love ur channel. Just a question what mic are u using?
i loved this ending, first concise video I've seen in a minute
BTW, the course is also available for R.
Thanks for sharing this amazing resource! Stanford's free data science book and course are invaluable for learners. Can't wait to dive in and expand my knowledge. Great find!
So true!!! This book is absolutely top notch and while there are other great reources out there such as Oreilly and Coursera, this book provides all the prerequisite knowledge
How nice that my Data Science course for engineering uses this book :)
I started Python about six months ago this ago. Before that DBA with extensive T-SQL programming experience. I tried that Stanford paper and I sure do not get the recommendation - way too complex and needlessly so for someone trying to learn the language. Python Institute’s intro books and testing worked for me
how to learn python quicly ?
So lucky to have found this video, I will find the book tomorrow morning and study it before work
Best book on machine learning.
Quick tip learn statistics first. Then learn mathematical statistics. The read a 100 page per month in 6 months you are ready .
Then build projects
what is the difference between statistics and mathematical statistics?
where is the complementary video course he is talking about?
When I was going through a data science boot camp, in 2021, the instructor recommended ISLR. I tossed it to the side, because I don't know R. I'm glad that a Python version was released. I suspect that Python has surpassed R in usage in the data analysis realm.
FYI:
The affiliate link for the amazon book is broken :(
This is good news! However, it seems the the online edX course is available only in R, not (yet?) in Python.
I like Python, and its far easier to master than R, but I use R in my work far more often than I use Python. This may just be a bias among my management, but the fact that I knew R, and Matlab and Mathematica coming out of University made getting my first data analyst job much easier.
@@markrussell4682how did you learn R.
Any book or course you would recommend to begginers?
@@markrussell4682 So would you recommend learning R instead of python or both or also Matlab?
@@deusvult1268 I think in most instances Python is a more useful language to know. Python is now interoperable with Microsoft Excel which is used almost ubiquitously in data science.
honestly the best advice on youtube i've ever seen
This book is amazing! I have already read the R one, but this in Python has the potential to be the best out there! Thank you for sharing this with us.
Which book
@@confidential303 which book?? where to find it?
Thank you Giles, the book is fantastic.
Can someone pls tell me the name of the book.
Sorry, I watched video and looked the links in description, but could not get the name of book.
Minute 3:39 An introduction to statistical learning. The link is also available in the description.
Are they still selling these think science book in library?
Always enjoy watching your videos!
Does he ever give the name of the book?
1:42 “make it stick: The Science of Successful Learning”? I will have to get my hands on that!
Always a pleasure listening & learning from You Bro! Little wonder you are successful at what you do!
he got a really nice and clear voice
But, where is a link to the book?
Hey heads up, update your recommendation to python crash course version 3 (in your description)
Can I have the link for this book? I can not find it in the infobox
What a resource! You've just gained a subscriber. And thank you to the authors Hastie, James, Taylor, Tibshirani, and Witten.
where is the link to the book?
QUESTION: how do I find non profit componies and charities to contact ?
Hello @Python Programmer. I may have missed the info, but is there a related course mentioned in the video?
Does anyone know where the answers to the exercises can be found? Just so I can check I'm on the right lines. Are they in the printed book perhaps?
So where’s the link to the book??
Thank you sir , the way you propose the scientific material is interesting.
One of the things I learned myself, is not to watch commercials.
the classic fatherly British docuseries presentation is of archetypal excellence
It was a famous book at my college. ISLR is what we called it.
The affiliate link for the book I believe is broken.
Giles, thx for sharing that "Make it stick" book again. I just went ahead and bought it through you affiliate link. Should have done it the first time you recommended it. Better late than never.
As the other commenters have pointed out, the authors couldn't charge for it even if they wanted to, because this project was publicly funded. They're legally obliged to make it free.
Where can I find answers to the exercise sections in the book?
Thanks for this hint. I downloaded it alredy for R and Python from the webpage. 👍
I will like to have the link to the book. Above all you are awesome.
ISL is definitely one of the best books for DS beginners! And now in Python!
Hi, I have the Hands on ML book. Which one of these two would you recommend me to read first?
Thanks for the video. Just letting you know that your affiliate link for the book "Make it Stick" is broken.
Link to the book please
Thanks for sharing, can one jump straight to the Python book or is it necessary to read both?
Both are the same. The only difference is Python and R.
Is this the course that Marc Tessier-Lavigne took?
Great vid! I wanna go learn it now!
Loved, Loved, Loved this Content. Thank You.
Brilliant video. Very short and informative. Well done ❤🎉
link to the book/course?
your affiliate link to Make It Stick is broken, but thanks for the recommendation!
Ebook recommended learn python (free) :
How to Think Like a Computer Scientist: Interactive Edition - Runestone Academy
Oh, I already have the book, but not the python version. Mine is in R. I am definitely uploading the python version ASAP. Also, brilliant isn’t free. Maybe they don’t charge much but definitely not free.
I actually came across both books yesterday before coming across this video.
So.. what is the book title then?
Hi, For some reason I can't download this book, is it only free in the UK?
Where can i get this book?????
It's an amazingly well written book
Hi
I don't see the link of the course
Can u provide it
Thanks
What should I offer for non-profit organizations? I assume they don’t know what data analysis can give them, and they probably don’t collect data.. Any suggestions?
Thanks for the video!
is there a link in the description to what he is talking about or am I just dumb?
One can apply for Omdena projects