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!! 🙌
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.
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
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😇
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.
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 ☺
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.
@@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.
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. ua-cam.com/video/hFLp_aP8iQQ/v-deo.html 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). 😀
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 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 🙂
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!)
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.
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?
Thank you for the "blood and tears" in making this video. It's a wonderful story. Thank you, and thank you Deepnote! I want to see your results, and look and play with your code. I am hoping it's in your Description above. Thank you, Miss Vu! You will be rewarded!!
I created a Deepnote account (FREE style), and duplicated your code. I am still learning from your video, Thu! The code is starting to make more sense (particularly the last part where it pulls the reviews and does text summarization). Fantastic!! Bye Bye :)
Cool video, though the title is pretty misleading. I don't really feel like you ever shared critical thought about what your analysis of these books said. This was more of a tutorial for hypothetically approaching this question by data analysis, but sort of left out the most important part which is actually consolidating your findings into something useful for others, and communicating those findings. No offense, the video is still very informative, and surely introduced me to some new topics I am happy to be aware of now, but I also don't feel like the video delivered what I was anticipating based on the title.
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.
Let's do some numbers. Say I have to analyse 1000 books - manually. I set up my time frame: 10 months for analysis. A week for creating bullets points, a table , whatever to get ready; and a week for finishing a vid with all the info. That would make 100 books a month. 3 books A DAY to go through to get a proper insight and take notes; to be productive, I set up time slots of 3 hours for a book, which makes it 9 hours a day of a hard work for my brain. For 10 MONTHS. Is it even possible? Not for me. Long live the hardware and software ❤
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
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!
Watched the entire video and still waiting for "What you found through it". Title is a clickbait for sure, making us think that you studied 1000 Data Science books.
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?
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????
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!! 🙌
Love how you walking through every step clearly. This inspired me to do my own project. Thank you
I love this kind of video that explains the data project step-by-step in a well-organized way. Learned a lot.
You have some of the most concise and clear tutorials. Really amazing content! 🔥. I always look forward to your posts
This made my day, Kyle! 🙌 it really took a loooot of work for those videos, so I’m super happy you enjoy them 🤩
That was a VERY USEFUL project. The presentation was also on point! Thanks for sharing!
Clear, concise and I really like how well you describe the algorithms and code. Easily can be adapted to other similar types of analysis.
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.
Thank you for this kind comment 🙌🏽
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.
Loved this! Especially the use of BERT for the summary; I may have to copy this for my next project!🙌🏼
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
@@Thuvu5 Cloud it is then! 🙌🏼🤣
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😇
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.
The best explainer ever.greetings from Kenya.Bring on more.
This is superb 🔥
Very Informative and concise! Thank you for creating this video
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 !
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 ☺
Aw that’s really cool to know! Thank you Palak! 🤗🙌
Oh my gosh!!! your content is pure gold!!!!! Thanks!!!
Thank you Gonzalo! I really appreciated it! 🙌🤗
Oh, btw, in a world of Kardashians I want to be a Thu Vu ❤️
That’s super sweet of you Stefany! 💖 I wish you the best in becoming whoever you want to become 🤗
@@Thuvu5 Please, do your "a day in life of a data scientist" video 💕 Please!!
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.
@@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.
Really, very informative and make my day !! Thannxxxxxxx
So glad to hear Sanjay! 🎉
Thanks so much Thu, this video is both fun and very instructive.😀
Fast-paced but still clear - very well done.
You're always on the cutting edge! 🔝
Thanks a lot! 🥰
I'll surely play around with Deepnote asap. 🤓
That’s awesome, Barbara! 🤗
Her content is amazing❤❤❤❤❤
Thank you. Really enjoyed this.
Thank you for introducing deepnote. I will take a look at it.
wow, thank you, very instructional, interesting and well done content!
Nicely explained ! Cheers !
"Thank you wikipedia"
That was funny 😂😂😂
Great video and explanation. Thank you
Brilliant! excellent work. thank you Thu Vu
Thank you for watching and commenting 🙌
I got my attention there when you said "finally to level 3 which is not for the faint hearted."
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.
ua-cam.com/video/hFLp_aP8iQQ/v-deo.html
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). 😀
thanks you 😀👍
Excellent video 👏👏 Need more such videos from you!
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 🙏🏾
Loved this video!!!!!!!!
I really love you and your videos..
Thanks a lot for ur work
Thank you for your love 🙌🤗
Very Unique Content making and intersting. Subscribed & followed on medium. 💙💙
Thank you 🙌🙌
Great content, lot of useful information. Thanks
This has a look & feel of Notion! Nice work love the vid!
Being able to read and focus is a gift now days
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.
That’s awesome Arif! 💪 Thank you so much for your kind words!
You are amazing for explaining code just amazing!
Love this! I just have one question, how did you get the data set?
Thank you so much for sharing
Amazing work.
Could you create a Data Science Bootcamp for beginners? I want to find a job as Data Analysis or Data Science, I’m civil engineer 😊
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!!
Now that's what I call creativity 💕
Always interesting! I can’t wait to learn python so I can come up with projects of my own 😅
Looking forward to hearing about your projects 💪😉
@@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 🙂
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!)
So much appreciated this, Giovanni! 🙌 Good luck with your project! Scraping is always fun! 🤩
I want a list of the 1000 Books you analyzed
getting a error in
KeyError Traceback (most recent call last)
Cell In [29], line 8
6 # Get prediction/ labels
7 labels = model.labels_
----> 8 book_cl = pd.DataFrame(list(zip(df['title'],labels)),columns=['title','cluster'])
9 print(book_cl.sort_values(by=['cluster']))
self._check_indexing_error(key)
KeyError: 'title'
Ko hiểu gì mà cảm thấy cuốn 😅
All Made in 🇺🇸😊
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.
That’s awesome 🤩🙌💪. Good luck with your new projects!
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?
and you spent 1000 seconds on these 1000 books...............🤣😂🤣
Amazing vid. Thanks for being such a great inspiration😊
Thank you for the "blood and tears" in making this video. It's a wonderful story. Thank you, and thank you Deepnote! I want to see your results, and look and play with your code. I am hoping it's in your Description above. Thank you, Miss Vu! You will be rewarded!!
I created a Deepnote account (FREE style), and duplicated your code. I am still learning from your video, Thu! The code is starting to make more sense (particularly the last part where it pulls the reviews and does text summarization). Fantastic!! Bye Bye :)
I loved this video! More of these please! 🙏
Another excellent video. Thanks very much!
Thanks!
Thanks!
Cool video, though the title is pretty misleading. I don't really feel like you ever shared critical thought about what your analysis of these books said. This was more of a tutorial for hypothetically approaching this question by data analysis, but sort of left out the most important part which is actually consolidating your findings into something useful for others, and communicating those findings.
No offense, the video is still very informative, and surely introduced me to some new topics I am happy to be aware of now, but I also don't feel like the video delivered what I was anticipating based on the title.
Really a serious stuff... thanks for sharing...
Excellent video！Thank you！
Do we ,only need Statistics concepts to deal with numbers to become a data analyst?? What other mathematical skills are required besides Statistics?
Best data senpai! Your videos are always amazing!
You put "Visualize This" in the Data Science category???
That's a really impressive project!
Great vídeo! What a good channel recommended the UA-cam algorithm today!
Wait, you reviewed these books based on their reviews below ? But you studied data science, how can you rely on what others say ?
This is the first time I've understood that I truly didn't understand anything, thanks !
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.
Glad it was helpful Pedro!
Great project and explained really well. Thank you for this. Ur content is worth the wait. 💯
Thank you Sukriti! I’m glad to hear. Sorry for the slow production of this kind of videos 😅
@@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.
This is amazing, thank you for sharing!
hey vu its awesome video. would you give me some ideas for projects in ML?
Your talking voice sounds really nice.. 😅❤
Really good! You also could do some hypothesis test with the scatter plots to support the idea
Let's do some numbers. Say I have to analyse 1000 books - manually. I set up my time frame: 10 months for analysis. A week for creating bullets points, a table , whatever to get ready; and a week for finishing a vid with all the info.
That would make 100 books a month. 3 books A DAY to go through to get a proper insight and take notes; to be productive, I set up time slots of 3 hours for a book, which makes it 9 hours a day of a hard work for my brain. For 10 MONTHS.
Is it even possible? Not for me.
Long live the hardware and software ❤
You are very sweet and yet effective!
I am a data analyst trainee can please suggest me some projects idea which helps me in my cv
Congrats for the video, an impressive data science work, and really useful in both ways!. Thanks!
Thanks you Jose! Really glad it was useful 🤗
Was looking for her recommendations on data science books… got lost
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
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!
Thanks for the video!
The editing makes it sound like a one massive monotone lecture.
Such a cool video. Love it!
This is one of your best vids!!! Thank you for the great work!! Badass!!! 😎
Aw that’s awesome to hear! 🎉 thank you so much!
As usual, very nice video 👌
My girlfriend quits at hello world
Super Interesting!
Ma'am, you're so smart! And so pretty too! 😍
Watched the entire video and still waiting for "What you found through it".
Title is a clickbait for sure, making us think that you studied 1000 Data Science books.
thank you Dear!
Rare useful result of women's study.
You're tremendous 😍
I'm totally fascinated.
Thank you
Best Python books, sounds like best cookbooks to make bread out of crap
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?
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????