I Analyzed 1000 Data Science Books on Amazon: Here's What I Found 🤓

🔗 Deepnote 👉 deepnote.com/
📚 This Deepnote project:
deepnote.com/workspace/thu-70...
🌐 The published article:
deepnote.com/@thu/Data-scienc...
Hi data nerds! 👋 In today’s video, I’ll be walking you through a project to analyse data science books using Deepnote. I think this is a fun project to work on to both sharpen our skills on multiple levels, and to get to know more about data science books available in the market. We’ll be doing exploratory data analysis, clustering book titles to find out the common themes, and finally scraping Amazon reviews and summarising the reviews for each book.
I hope you enjoy this video 😄.
🔑 TIMESTAMPS
================================
0:00 - Intro
0:28 - Which analyses we will be doing
1:46 - Intro to Deepnote
4:41 - Dataset
5:27 - LEVEL 1 - Exploratory data analysis
8:24 - LEVEL 2 - Clustering book titles
17:19 - LEVEL 3 - Amazon review scraping & Review summarization
21:44 - Publish notebook to article and app
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#datascience #machinelearning #DataAnalysis #Datanerd #ThuVu #dataanalytics

[@AM-ze4hr]

Clear, concise and I really like how well you describe the algorithms and code. Easily can be adapted to other similar types of analysis.

[@lnli3478]

I love this kind of video that explains the data project step-by-step in a well-organized way. Learned a lot.

[@lorenzo6777]

Love how you made a 23min video feel like just 10min. Other channels I’ve come across show the abstract or theoretical uses of data science techniques, but I love this real world application use!! 🙌

[@palakgoel5656]

This is literally so cool! 🙌 I'm learning so much from this channel and the fact that it is all so applicable to real world problems only makes me more fascinated by data analytics and you get the credit Thu! Thank you ☺

[@Thuvu5]

Aw that’s really cool to know! Thank you Palak! 🤗🙌

[@peperiday]

Love how you walking through every step clearly. This inspired me to do my own project. Thank you

[@Pakman909]

You have some of the most concise and clear tutorials. Really amazing content! 🔥. I always look forward to your posts

[@Thuvu5]

This made my day, Kyle! 🙌 it really took a loooot of work for those videos, so I’m super happy you enjoy them 🤩

[@uriastriumph4780]

Love this so much... Learned a whole lot and I'm sure I would learn more when I get back to it again... Thanks Thu 🙏🏾

[@ajay_garg]

Hello Thu. First of all, I want to thank you for this amazing video. I have learned a lot from this single video and the great thing is that I can apply a lot of these concepts (kmeans and tokenizers etc.) in other projects too. I have followed along with this video and tried to build the same project. I got some problems on the way which I tried to handle and solved many of them like I could not get wordcloud to install in my windows laptop, so I used bubbles chart from matplotlib to plot top 20 occuring words in each cluster and many others like these. I also scraped all the reviews. Since I was doing all this on my local machine, I had to shutdown the kernel for a while. After some time, when I reopened the notebook and ran all the cells, everything worked smoothly except that I was only able to get reviews for about 170 books but urls for more than 750 books are available. I tried scraping one of the random urls one at a time and got some weird response like connect to our APIs. I am not very comfortable working with APIs right now and I don't understand why I was able to scrape reviews before and not after. Once again, a great video and I have watched many of your videos and they are all great. Thankyou.

[@willykitheka7618]

That was a VERY USEFUL project. The presentation was also on point! Thanks for sharing!

[@ahoudouidrissou8491]

This is my first time on your channel and I find your work fabulous. You have a particular way of explaining and I love that. I wish all the best.

[@Thuvu5]

Thank you for this kind comment 🙌🏽

[@LukeBarousse]

Loved this! Especially the use of BERT for the summary; I may have to copy this for my next project!🙌🏼

[@Thuvu5]

Haha thank you Luke! Don’t blame me if it freezes your laptop because it does use quite a bit of memory for large text data 🤦‍♀️. Cloud would def be safer

[@LukeBarousse]

@@Thuvu5 Cloud it is then! 🙌🏼🤣

[@dxim86]

This is superb 🔥 Very Informative and concise! Thank you for creating this video

[@arifbudiman9975]

Wow your explanation is really good, it flows naturally and interestingly after hearing you I become more motivated to pick up DS/ML again. You're a good teacher.

[@Thuvu5]

That’s awesome Arif! 💪 Thank you so much for your kind words!

[@ElBarrabasVK]

Really good! You also could do some hypothesis test with the scatter plots to support the idea

[@giovannitertulli4962]

This is one hell of a crazy good video. I am currently tackling my first scraping/viz project, and I got so many good tips here. Amazing content (not only this video, but all the others too, which I’ve binge watched btw!)

[@Thuvu5]

So much appreciated this, Giovanni! 🙌 Good luck with your project! Scraping is always fun! 🤩

[@venkatprasath01]

Excellent video 👏👏 Need more such videos from you!

[@paulflute]

I have absolutely no idea what so ever how i got here or what you are talking about.. yet i watched 8 minutes in fascination at your level of clarity and skill..

[@daviddjames_]

This has a look & feel of Notion! Nice work love the vid!

[@andresnarvaez4957]

Thanks so much Thu, this video is both fun and very instructive.😀

[@anubratasahoo4202]

Usually data science is so boring to watch,but i really enjoyed this video.♥️ You can share some more analysis or tutorial...on data science. It's very fun to watch.

[@fredieeevlogs7077]

Wooow I loved your video!!! is amazing how thin video keep me interested to the end, 😍. Also your explanation was clear and concise. Thank you!!

[@EvilCherry3]

Lol right on time for me ! ^^ I start learning NLP this month and plan to clusterize the results at the end. Bravo for this very pedagogic video !

[@sherifffruitfly]

Fast-paced but still clear - very well done.

[@jorgeolivera9095]

I loved this video! More of these please! 🙏

[@YN-wv1rd]

Thank you for introducing deepnote. I will take a look at it.

[@guilhermegoncalves7235]

Best data senpai! Your videos are always amazing!

[@abkulorto7403]

The best explainer ever.greetings from Kenya.Bring on more.

[@sazopro]

This is one of your best vids!!! Thank you for the great work!! Badass!!! 😎

[@Thuvu5]

Aw that’s awesome to hear! 🎉 thank you so much!

[@atenciop123y]

Wonderful video. I’m going to use this video to create my own project to showcase my skills. Thanks so much for helping us us learn all these techniques.

[@Thuvu5]

Glad it was helpful Pedro!

[@finnam]

I must say this is the best hand-on tutorial ever. I am learning how to do textual analysis (seft learning) and it is really frustrated since free and open source is really fragile, incomplete, or really hard to follow. Maybe I did not find a good source untill now. Thanks a lot. I first do everything follow your video step by step and will soon impliment these for my own project or on something I am interested in. Again, I am really appreciate your work.

[@Thuvu5]

That’s awesome 🤩🙌💪. Good luck with your new projects!

[@MrBenStringer]

Amazing vid. Thanks for being such a great inspiration😊

[@astatinitehelmet]

Such a cool video. Love it!

[@alex_suero]

This is amazing, thank you for sharing!

[@josegimb7220]

Congrats for the video, an impressive data science work, and really useful in both ways!. Thanks!

[@Thuvu5]

Thanks you Jose! Really glad it was useful 🤗

[@loresowhat]

Wow this is absolutely fantastic and also got to know how to use different ML concepts in a practical way!! keep up with the work and will definitely try to do something similar on my channel😇

[@jasonwoodward5501]

Thank you. Really enjoyed this.

[@SukritiShah_28]

Great project and explained really well. Thank you for this. Ur content is worth the wait. 💯

[@Thuvu5]

Thank you Sukriti! I’m glad to hear. Sorry for the slow production of this kind of videos 😅

[@SukritiShah_28]

@@Thuvu5 Don't be sorry. I'm glad I found this channel and will happily wait for the quality videos on data science in future too.

[@SanjaySingh-jo3py]

Really, very informative and make my day !! Thannxxxxxxx

[@Thuvu5]

So glad to hear Sanjay! 🎉

[@gonzaloamadorhernandez7020]

Oh my gosh!!! your content is pure gold!!!!! Thanks!!!

[@Thuvu5]

Thank you Gonzalo! I really appreciated it! 🙌🤗

[@cerealport2726]

Another excellent video. Thanks very much!

[@karticsarin8063]

Nicely explained ! Cheers !

[@davidvanderbyl904]

Love this! I just have one question, how did you get the data set?

[@laura_uzcategui]

Great video and explanation. Thank you

[@peterthornton4462]

wow, thank you, very instructional, interesting and well done content!

[@mahendrakumargohil6384]

Great video Ma'am, beautifully explained and very crisp. 😀

[@Barbara-ka1mt]

You're always on the cutting edge! 🔝 Thanks a lot! 🥰 I'll surely play around with Deepnote asap. 🤓

[@Thuvu5]

That’s awesome, Barbara! 🤗

[@martinweston3177]

A brilliant video. So easy to follow and introduced me to so many concepts.

[@Thuvu5]

Thank you Martin 🙌. I was a little bit afraid it went a bit too fast and hard to understand 😅

[@bigdhav]

Awesome video! Thank you!

[@VRI81]

Loved this video!!!!!!!!

[@lawofattractionspace]

Great content, lot of useful information. Thanks

[@ekaterinavolkova4348]

I've never heard about Deepnote. Thanks for recommendation.

[@EdgarOlivos]

Great vídeo! What a good channel recommended the KZbin algorithm today!

[@abhishekpatil7336]

You are amazing for explaining code just amazing!

[@pronodbharatiya6412]

Really a serious stuff... thanks for sharing...

[@AllthingsFoodieTX]

Being able to read and focus is a gift now days

[@merekissagalyev5994]

I really love you and your videos.. Thanks a lot for ur work

[@Thuvu5]

Thank you for your love 🙌🤗

[@rogercortes1676]

As usual, very nice video 👌

[@DG-ju2wf]

Brilliant! excellent work. thank you Thu Vu

[@Thuvu5]

Thank you for watching and commenting 🙌

[@bixinyu3117]

Excellent video！Thank you！

[@onyx8620]

Thank you so much for your fruitful videos. I would like to request your another videos in related with AHP if I have a chance.

[@tommyhuffman7499]

That's a really impressive project!

[@mohamedbelazreg9949]

This is the first time I've understood that I truly didn't understand anything, thanks !

[@mohammednadjiballahsalhi704]

Thank you so much for sharing

[@RonanAzarias]

I made a blinking look at the best ml books list and I think that maybe found some biases in it. First, some books are free and available by the authors, so after reading the material for free and liking it, then the user could decide to buy a physical one and make a better review. The first ones are relatively cheap, so being more accessible could be read by more users and receive more good notes. Taking a look at the "price vs. reviews" plot there is a concentration of reviews between ~15-60 prices. So for me, the I'm best MLbooks list is about the best "accessible" ML books. I thinking if this is caused by the dataset itself since the note of the review came abstracted from begin.

[@stefanyloren]

You're tremendous 😍 I'm totally fascinated. Thank you

[@arshdeepsinghbrar4148]

Her content is amazing❤❤❤❤❤

[@kareer4genz]

Very Unique Content making and intersting. Subscribed & followed on medium. 💙💙

[@Thuvu5]

Thank you 🙌🙌

[@alieninstallation50]

Thanks for the video!

[@stefanyloren]

Oh, btw, in a world of Kardashians I want to be a Thu Vu ❤️

[@Thuvu5]

That’s super sweet of you Stefany! 💖 I wish you the best in becoming whoever you want to become 🤗

[@stefanyloren]

@@Thuvu5 Please, do your "a day in life of a data scientist" video 💕 Please!!

[@theloniousMac]

While I completely agree with your sentiment, one should be aware that the world is not filled with Kardashians, and maybe if it was it might be a better place. The Kardashians have provided significant financial assistance to families in need, numbering in the thousands. They have helped to provide clean drinking water to areas of Africa with limited access to water. These are just some of their charitable actions. I’m just saying that they take a great deal of criticism and get little credit for the good they do.

[@stefanyloren]

@@theloniousMac Of course, I'm aware that the world is not filled with Kardashians, my words are not literal. And that's great they do these things; I've heard a bit about it, but it's great to know more of that. However, what I wanted to say is the world (or media) is full of Kardashians-wannabe. The Kardashians promote dangerous beauty standards, that lead girls to feel bad about their bodies and to try to get the appearance they have. Now, the girls want to have big booties, big lips, big boobs, hips, small waists... look like a Kardashian. I have a friend that is beautiful and have a beautiful body, I admire her body figure, like a guitar, buuuut all the time she feels bad about her body, and her face. She wants to look like Kendal Jenner. I have sent her images where she can see how Kendall's photos are photoshopped, but, still, she wants to look like her; she, and other friends of mine. That's bad. I watched KUWTK, almost all the reality, and I loved it. I like Kim and admire her a lot, in fact, I admire her mother's business skills. But I cannot be blind and don't see that what they promote is hurting the self-esteem of many girls and women in the world.

[@relytheone853]

Would you make a video about the math that data science needs in order to comprehend it fully.

[@chayanitbhateja7964]

I got my attention there when you said "finally to level 3 which is not for the faint hearted."

[@taiwoadewumi7900]

Now that's what I call creativity 💕

[@ketanpande2297]

hey vu its awesome video. would you give me some ideas for projects in ML?

[@bobzieian11]

You could be a teacher at a university if you keep at it. Im at the start of my data science journey in final year of uni Bsc Finance and business. Your presentation and delivery is excellent I appreciate this video so much. I feel a lot of youtubers nowadays avoid showing the working process and just brag in a gatekeeping patronising way. You have provided a lot of hope. Thank you i am now a supporter

[@Atlas92936]

Don’t be afraid to ask questions. I’ll be taking an ML class in my final year at college. I know it’s gonna be filled with computer science students and I will feel behind. I had to tell my ego there’s No such thing as dumb questions!

[@p.u.t.a]

You are one of world best in the sharing experience that I have ever know. Thank you so much

[@Thuvu5]

Aw chị cám ơn em rất nhiều 💖

[@muskanrath7125]

Can you also please post videos data visualisation using tableau if possible? It would be really helpful if you could please share resources you prefer on artificial intelligence, nlp.

[@alexgeld7173]

Always interesting! I can’t wait to learn python so I can come up with projects of my own 😅

[@Thuvu5]

Looking forward to hearing about your projects 💪😉

[@alexgeld7173]

@@Thuvu5 I'm doing a bootcamp at the moment, however once I get through I will start experimenting with Automate the boring stuff and Python crash course books 🙂

[@uriastriumph4780]

"Thank you wikipedia" That was funny 😂😂😂

[@lepetitephuc5164]

Đọc sach nhiều dữ như mọt sach vay Thu! Do you have and recommend which should be your fav programming language? Is this Python your favorite programming language Thu?

[@jimcallahan448]

Awesome video! 1. Introducing Deepnote - similar to Google Colab, but with more collaberation features 2. Pandas -- My recollection is Pandas just displays data type at top, yet when you printed the data frame there was a summary and a graph -- was this a result of the Pandas version, a Pandas option or DeepNote? 3. K-Means Clustering - you used an "elbow method" (graph) to determine number of clusters 4. Web scraping 5. Text analysis including tl-df and wordcloud (you made it look easy ;) The video seemed very fast paced (I checked I wasn't runing it at 1.25x) did you speed it up or were you talking that fast? (or am I just slow -- I tend to think slower when doing data science) Also, could you come up with a top N list for each of the 6 clusters? (what were the top rated books in each cluster?) On other topics: Coursera just posted a link on FaceBook to this old (but useful) blog on Coursera's note taking features. blog.coursera.org/ready-for-retention-presenting-a-unified-note-taking-experience/ I just bought an iPad and will have to re-watch your video on notetaking with an iPad. kzbin.info/www/bejne/nnevoZKXhZ2ch7M In Florida, we just had an election on Tuesday and a hurricane on Wednesday/Thursday, looking forward to getting back to Machine Learning with Andrew Ng (thanks for recomending it). 😀

[@mickolesmana5899]

i came here expecting to someone explain in the usual speech presentation-esque manners but found out that she explained it in pandas and notebook. Surprised to be sure but a welcome one.

[@iliovininino]

Great video! Besides you explain very gently, kindly and in a concise manner. +1 sub, keep up the good work!!! AlALso you seem to be a very kind person and you look stunning. On the other hand, the content of the video made me realize how far I am of your profesional level. How long did it took you to gain your current knowledge????

[@athanasiospapoutsis9978]

Super Interesting!

[@manidoowilkie8459]

Anyone have any solutions to this? I am using the same csv file from kraggle as the one in this video, but I seem to be erroring out on scatter. It wasn't able to scatter the data because of NaN values. I filled them in as zero, but now the scatter looks like it's very skewed towards 0

[@coonnaarr1984]

I want a list of the 1000 Books you analyzed

[@linkernick5379]

Hi, Vu! Thanks for the video. May I ask a question? There is the new kid on the block to do EDA, the library called Polars. The authors claim it is much more efficient than Pandas. Have you ever look at it maybe?

[@Thuvu5]

Hmm I’m not familiar with that library unfortunately 🤔

[@frankmwale1580]

You are amazing!

[@dinosilooy2228]

What a great project!

[@arvdosal]

Brilliant!!!

[@MrKrtek00]

great little project

[@MarcBenkert001]

Thanks!

[@anandhuvenu3643]

Hey which laptop do you use..?

[@Brian-qv5ze]

Cảm ơn video của chị nhiều nhé 👍Love your contents

[@Selfbeliever252]

Can you suggest me the best laptop to buy? (No limited budget)

[@qwertyqart]

do you think doing the same on goodreads would be helpful to check the reviews as well?

[@Thuvu5]

Yes definitely! I use it all the time

[@unknown_seekerX]

hi, I like the video but here is a trick. When you select machine learning books, you only considered books whose title contains 'Machine Learning'. Some titles contain one of ['ML', 'Machine learning', 'machine learning']. If you check their indices, they are different. That means your set of machine learning books is only a part of all machine learning books. I don't know how to attach an image here to my analysis. Can you share simple ways to cover all those ML-string variations in one line?

[@Digital-Light]

thank you Dear!

[@carloscabrerahernandez3663]

great vid

[@MRBAM]

thanks you 😀👍

[@fernandourrutia2566]

Amazing !