This video took me an *exponential* amount of time to edit, which is beyond my *limit* (bad math puns 😅). Please show it some love and let me know your thoughts/ questions/ struggles below! 🙌🏽
@@amanthinks374 Hey, the app I use is Notion 🙂. And the OneNote notebook is not mine so I'm afraid I can't share it with you. Stavros created it and the MIT course is a paid program so I don't think it's possible to share it freely.
Thank you so much for the video. I have just started in DS and this came at the right time. I would like to know if you could make a video on the industry or application based side of data science as my focus too is on that end.
@@Thuvu5 @Os Med Surry for not being able to share the Notebook with you, unfortunately its proprietary paid learning material that we are not allowed to distribute. Thank you for your interest and attention to detail :) Best regards. Stavros
Really ? I was very bad at maths but now I want to learn it more in the order to become à data analyst. I had a very bad marks to my exams but I will try hard
@@cutiegirl3400 Don't let your previous performance define you. Those were different circumstances, settings and you were even a different person. Just focus on learning to be a better data professional and have fun with it.
I used to be keen on and really good at math at my high school. Unfortunately, I wasnt taught math, economics, or tech..., bc I studied at Journalism and communication university. So am I able to transfer to Data industry?
The "Math for Data Science" guide, we all need!!! 🔥🙌🏼🔥 Thu, the level of work and detail you put into this video is insane. 🤯 More vids like this, plz! 👏🏼
Thank you Luke 🙌🏽, yeah this video took me too long to make haha. I was agonizing over many details in the video along the way as well. Really happy you liked it! 🤩
Great tips! Especially about your points around a note taking system and coding the math. When I started my journey, it took me a few months to realize my note taking system was horrid that I wasn’t retaining and needed a better note taking system. I also moved to electronic vs hand written. Coding the algorithm from scratch in python was also key. Patience was so key, many times I wanted to jump to the end result w/o understanding the algorithm itself.
Hey there, thanks so much for sharing your experience!! 🙌 indeed patience is key when learning how things actually work. It’s frustrating sometimes, but I feel like the process is also rewarding in itself..
I just discovered your excellent videos and I binge-watched them last night. I love the way you explain things. I was thrilled that you recommended my "Data Science Math Skills" course - it's my best effort to leave out all the hard stuff beginners don't need to get started.
Omg are you Daniel Egger? It’s such a pleasure to have you checking out my videos! 🤩. It’s a great course for beginners, I loved how digestible and effective it is! Thank you so much for creating the course! And also, thank you for your kind words on my channel 😃🙌
This was super reassuring. It does feel a lot easier to learn things nowadays since we can find 100 different explanations online instead of only relying on a teacher and a book
Hey Chanin! Thanks for stopping by! 🤩 I’m using Final Cut Pro. And what are you using atm? Thanks for your kind words on the video, I really appreciate it! And yeah, filming B-roll is actually more fun to me than filming A-roll, so I just like to do more of it 🙈
@@Thuvu5 Thanks for the info. I’m currently using Premiere Pro, though I am also playing around with Final Cut Pro. It’s always fun to learn what fellow creators are using for content creation. :)
Ah I see! I’ve never used Pr before. But I guess the 2 software are very similar as to what they can do. Yeah absolutely, i also love poking around to know what people use for their videos, and researching gear 😂
Thank you for such great tips in learning Mathematics for DS, Thu. I was lost in the maze of math and statistics for DS; your video did shed some light on the learning path and how to structure these complicated concepts for later reference
This is one of the best clear cut video, people who scare about the internal math of ml model can get confidence to learn after watching this video. Thanks much sharing madam, please do post more !!!!
All the people that currently is teaching, (making videos or producing material), know about how hard is to produce it, so thank you. I encourage you to continue doing it, best. Jo
Thanks a lot for putting together this guide! It gave me a good overview of what I might need to dive into if I decide to tackle the new course by Andrew Ng. Highly appreciate your effort! 🙏
Fabulous. I especially liked the animations of linear algebra things that flew by. I also liked your brief discussion of imposter syndrome ("don't act on it") vs enthusiasm ("take action on it"). Finally, I appreciated you saying that you're not smart enough to do research... for me, realizing that I am really not as smart as I thought or imagined myself to be has been helpful in "getting real", without falling down the pit of imposter syndrome.
Hey John, thanks so much for sharing your thoughts! Indeed, I feel like we should appreciate our other strengths as well and there’s no need to feel imposter 🙌
Critical thinking and meditation after discovering or observing new technics helps to retain math calculation, algorithm , procedures in the brain , it can be applied to data science fields or other fields that involves mathematics
I found discrete mathematics, which I *did not* learn in university, irreplaceably useful for my CS courses. (Udemy, Amoure.) I did actually complete "Mathematics for Machine Learning". Great style of teaching! Wouldn't be able to do it on my own.
The timing on this. I've just picked up a book on linear algebra and Calc and have been grinding at it. I love your car analogy, tho I'd like to expand on that. Hobbyist aside, it can be useful to have a further understanding on how stuff works because say, if your car breaks down in the middle of the road, knowing how some parts works can help you diagnose and sometimes even fix the issue you run into yourself. Ofc this isn't necessary to drive a car, but it's a parallel progression imo, if you know more, you have an edge over people who don't 😎
Absolutely agreed Sethi! Especially if you drive the car in the middle of desert 😂. It’s indeed always good to know how to diagnose the issues and potentially fix them or know where to get help 🙌
Awesome video Thu Vu! Your comments on the end of the vídeo about the impostor feeling and about the understanding vs explanation is just perfect! Ty for the amazing content.
Glad you enjoyed it! 🙌🏽 Yeah, the impostor feeling is so universal and hard to befriend. Glad you found it useful what I talked about 😇. Thank you for tuning in!
When I encounter new topics I don't note them 😢, that's why after a few days I forget those topics. Thanks Thu Vu for marking the point , this video was great.
Thank you, Kevin! Really glad you enjoyed it! 🙌🏽 And yes, absolutely agreed with you about the libraries nowadays! I love them but still quite often had to dig into their documentation just to be sure what they actually do 😅
Thank you for the wonderful video. Although I have learned most of the Math you mentioned in my electronic engineering course, the video is still very interesting and helpful.
You go girl! I love your channel. Thank you SO much for making it. Its great to see other smart women. Again thank you and do your thing! Keep the videos coming 🙂
Hello! So this is my second watch on your channel and I must say you make really good content. Data Science is too much for me so I learn mainly for Data Analysis. I want to learn Mathematics for Data Analysis. Nowadays most of my learning constitute Statistical Analysis and some probability related parts. I am learning it in R from a book. I started to get interest in the beginning but after coming across different testing methods like ANOVA etc. it started feeling boring 😅 personally I was weak in mathematics during my school time and sometimes it feels like I am taking a wrong way by going towards analytics haha...like at some point of my career journey mathematical nightmares will haunt me lol
Hi Vivek, thank you so much! I can relate to the feeling of getting bored when learning too many statistical testing methods (that I'd probably never use)! I'd say it's okay to rotate among a few different topics and come back to this topic later, maybe you'll then feel more excited to learn it 🤓
This is a great video, I think a lot of people are scared of statistics until they start to need them, or use them in ways that are relevant for their own data.
Thank you so much for your usefult guidance. Hope you can extend your channel and wide spread the your inspire along data to everyone, from a developer in Vietnam
Well it really depends on what you want to do with data science. If are in research then you probably need more maths than coding skills. There is crazy tensor algebra if you want to modify the reverse AD without using torch.autograd.
Very courageous the way to present your ideas and recommendations and specially you experiences to encourage people!. Excellent content, very wise. Congratulations! I'm sharing you videos with my son's who are going to school. How immensely wrong were the people that put you down when younger. She on them.
Awesome Video Thu Vu! Thanks for the tips! I think that a good resource for statistics learning with python is the book Practical Statistics for Data Scientists by Peter Bruce, it presents the essential knowledge with applications in python and R as well.
Thank you for the book recommendation, Joao!! Oh it seems like a very good book, it actually popped up sometimes on my Amazon page and I didn't pay attention. Awesome! I'll check it out! 👋
Youre not wrong. Theoretical Math, Physics, Chemistry and Engineering are wayy harder than programming because youre discovering/inventing the science wile trying to solve daily tech problems. Programmer dont understand this.
@@FaruqAtilola I am a EE grad who left engineering and quantitative work many years ago. I go back to school to do a masters in DS and I feel right at home with the math. DS students often ask, how much math do you need to know for DS? My response is, you need to know just a little more than your competition, but your competition will often be engineers.
Thank you for poping into my feed and give me an anxiety strike… but seriously, great video, I do recommend the MIT open course, they have a great selection of courseworks
Hi Thu Vu! Just started watching your videos and found peace on them, I just graduated six months ago from a BsC on Financial Engineering, focused on Data Science and found my passion on ML. It is overwhelming wanting to know everything sometimes, but now I am taking one step at a time. I started working on a fintech startup but being the only DS Engineer over there is making the journey lonely. Even if I am expanding my portfolio and doing a lot of interesting courses I want to know if you (or anybody) have any recommendations on communities or "social networks" for expanding my DS network and getting interaction, rather than just following big names on LinkedIn, as of now I consider myself a student. Greetings from México!
Hey Fernando, I can relate to the lonely feeling you're experiencing. think there are a lot of communities out there. I used to join local Data science Meetups in Amsterdam to meet and talk to people. Online there are also a lot of Discord communities (for example Tina Huang has one of her own). Greetings from the Netherlands! 👋
I’m afraid I need permission from Stavros to share it. Also it’s a paid course so in a sense, it’s not advisable to share it freely on the internet. But I hope Stavros will update us soon about this in the pinned comment 🙂
ICL prof cert in A.I & M.L was a complete waste of money. I spent £4000 and thankfully got it refunded halfway through. Thanks for the vids really enjoying your content
Stats is a weird one. _Probability_ is definitely mathematical, since Kolmogorov's formulation is basically just a normed measure of event space. Also LLN, the properties of the distributions and their relation to eachother, statistical moments of sampled data formulas are all a priori. Bayes factor maybe, but that's not so much empirical, it's more just a matter of judgement when to use it.
I agree that there are many things we studied at college may not be useful in real world settings. But as a student, it is a good training process by taking hard core subjects to build up a sophisticated brain 🧠😁
You, and I mean everyone of you hopefully reading this comment, must use every single algorithm or mathematical concept on a particular problem within a particular context. So if you want to learn calculus/backpropagation/naive Bayes classifiers etc then define yourself a problem or search for a problem were the algorithm you want to understand already used. Then search for an already got documented and commented jupyter notebook and go for it step by step and do your notes. I also recommend TorchStudio to see what happens with your data on detail and what training parameters really do with your tensors. Ok, my tips tend to be a little bit machine learning-ish but whatever. If you try to learn something without context in this field you will end in a big frustration with math. Just my 2 cents.
I believe you had skipped couple of mathematical concepts like Manhattan Distance, SVD, etc ... Math is much needed for Machine Learning if not for "Applied Machine Learning". Coursera course Algebra for Engineers from Hong Kong University (the same is available on TH-cam) helped me to basic mathematics...
I really enjoy your videos Thu! Very insightful you latest one! I was always wondering how much Python should one need to know for an entry level data analyst position. Someone should know Python at intermediate or advanced level ... of course the more the better but are there really any minimum requirements? Will it be helpful for his/her role to know OOP with Python and advanced data structures (i.e. stacks, queues and linked lists)?
Hey there, thanks! For an entry level data analyst position I think an intermediate Python level should be ok. OOP and advanced data structures might not be necessary, unless you are doing really intensive programming stuff in your job, like building applications or data engineering
This video took me an *exponential* amount of time to edit, which is beyond my *limit* (bad math puns 😅). Please show it some love and let me know your thoughts/ questions/ struggles below! 🙌🏽
Can you please provide a link to the platform you use to take notes? And share the one note notebook with notes from the MIT courses? Thanks!
@@amanthinks374 Hey, the app I use is Notion 🙂. And the OneNote notebook is not mine so I'm afraid I can't share it with you. Stavros created it and the MIT course is a paid program so I don't think it's possible to share it freely.
Thank you so much for the video. I have just started in DS and this came at the right time. I would like to know if you could make a video on the industry or application based side of data science as my focus too is on that end.
Can you just come teach me 😭 haha
@@Thuvu5 @Os Med Surry for not being able to share the Notebook with you, unfortunately its proprietary paid learning material that we are not allowed to distribute. Thank you for your interest and attention to detail :) Best regards. Stavros
Maths is scary but when you learn maths with Data Science perspective, it actually starts making sense and you find it interesting!
Really ? I was very bad at maths but now I want to learn it more in the order to become à data analyst.
I had a very bad marks to my exams but I will try hard
@@cutiegirl3400 all the best 👍💯
@@wthxrsh thank you very much ! Do you have any advice on how to improve?
@@cutiegirl3400 Don't let your previous performance define you. Those were different circumstances, settings and you were even a different person. Just focus on learning to be a better data professional and have fun with it.
I used to be keen on and really good at math at my high school. Unfortunately, I wasnt taught math, economics, or tech..., bc I studied at Journalism and communication university. So am I able to transfer to Data industry?
The "Math for Data Science" guide, we all need!!! 🔥🙌🏼🔥
Thu, the level of work and detail you put into this video is insane. 🤯 More vids like this, plz! 👏🏼
Louder Luke!!!
Thank you Luke 🙌🏽, yeah this video took me too long to make haha. I was agonizing over many details in the video along the way as well. Really happy you liked it! 🤩
Thanks for your videos. You do a great job.
Thank you so much for your support Jeff! 🙌🙏
Great tips! Especially about your points around a note taking system and coding the math. When I started my journey, it took me a few months to realize my note taking system was horrid that I wasn’t retaining and needed a better note taking system. I also moved to electronic vs hand written. Coding the algorithm from scratch in python was also key. Patience was so key, many times I wanted to jump to the end result w/o understanding the algorithm itself.
Hey there, thanks so much for sharing your experience!! 🙌 indeed patience is key when learning how things actually work. It’s frustrating sometimes, but I feel like the process is also rewarding in itself..
I just discovered your excellent videos and I binge-watched them last night. I love the way you explain things. I was thrilled that you recommended my "Data Science Math Skills" course - it's my best effort to leave out all the hard stuff beginners don't need to get started.
Omg are you Daniel Egger? It’s such a pleasure to have you checking out my videos! 🤩. It’s a great course for beginners, I loved how digestible and effective it is! Thank you so much for creating the course! And also, thank you for your kind words on my channel 😃🙌
Thanks!
Thank you so much for your support! ❤️🙌
This was super reassuring. It does feel a lot easier to learn things nowadays since we can find 100 different explanations online instead of only relying on a teacher and a book
Thu Vu, the editing is next level and the there's so much B-roll, really cool. Just wondering, are you using Premiere Pro or Final Cut Pro?
Hey Chanin! Thanks for stopping by! 🤩 I’m using Final Cut Pro. And what are you using atm? Thanks for your kind words on the video, I really appreciate it! And yeah, filming B-roll is actually more fun to me than filming A-roll, so I just like to do more of it 🙈
@@Thuvu5 Thanks for the info. I’m currently using Premiere Pro, though I am also playing around with Final Cut Pro. It’s always fun to learn what fellow creators are using for content creation. :)
Ah I see! I’ve never used Pr before. But I guess the 2 software are very similar as to what they can do. Yeah absolutely, i also love poking around to know what people use for their videos, and researching gear 😂
Great job verbalizing the learning process! This video took thoughts out of my brain 🧠 in a really structured way. 🙌💯
Aw thank you so much!! Great to know that I could read your brain 😉😉. Thanks for watching! 🙌🏽
Your videos are truly amazing the editing, quality
You even told us about the topics which we are supposed to dig deep into along with the tips
Aw thanks for this Anurag! I really appreciate it! 👋
Thank you for such great tips in learning Mathematics for DS, Thu. I was lost in the maze of math and statistics for DS; your video did shed some light on the learning path and how to structure these complicated concepts for later reference
This is one of the best clear cut video, people who scare about the internal math of ml model can get confidence to learn after watching this video. Thanks much sharing madam, please do post more !!!!
This is a great overview, thanks for making it!
Great to hear Anita 👋
All the people that currently is teaching, (making videos or producing material), know about how hard is to produce it, so thank you. I encourage you to continue doing it, best. Jo
Thank you Jo!! Indeed it’s not easy, I feel like I learn a ton myself from producing these contents. All the best! 🙌
Thanks a lot for putting together this guide! It gave me a good overview of what I might need to dive into if I decide to tackle the new course by Andrew Ng. Highly appreciate your effort! 🙏
for calculus and linear algebra, they are more important in machine learning especially deep leaning
Thank you so much for giving clarity in what things we should focus on. I was totally confused since I am a beginner in data science. ❤️❤️❤️
Fabulous. I especially liked the animations of linear algebra things that flew by.
I also liked your brief discussion of imposter syndrome ("don't act on it") vs enthusiasm ("take action on it").
Finally, I appreciated you saying that you're not smart enough to do research... for me, realizing that I am really not as smart as I thought or imagined myself to be has been helpful in "getting real", without falling down the pit of imposter syndrome.
Hey John, thanks so much for sharing your thoughts! Indeed, I feel like we should appreciate our other strengths as well and there’s no need to feel imposter 🙌
Love the video and effort you put into it 👏
Hey Sundas 👋! Thank you so much for tuning in! So glad you enjoyed it - and heck yeah, this one took me way too much time to make 🤦🏻♀️
Great animation and content and delivery, gr8 channel , thanks🙌
It is an amazing channel. Every data scientist should start from here. Keep your tremendous effort for the very important topic.
That's so kind of you! Thank you 🤩
Critical thinking and meditation after discovering or observing new technics helps to retain math calculation, algorithm , procedures in the brain , it can be applied to data science fields or other fields that involves mathematics
Brilliant summary! This is the first time I've come across your channel and I have subscribed now!
That’s awesome!! 🤩 welcome to the club! 🙌
I found discrete mathematics, which I *did not* learn in university, irreplaceably useful for my CS courses. (Udemy, Amoure.)
I did actually complete "Mathematics for Machine Learning". Great style of teaching! Wouldn't be able to do it on my own.
Thanks so much for sharing this Andrew!
The timing on this. I've just picked up a book on linear algebra and Calc and have been grinding at it.
I love your car analogy, tho I'd like to expand on that. Hobbyist aside, it can be useful to have a further understanding on how stuff works because say, if your car breaks down in the middle of the road, knowing how some parts works can help you diagnose and sometimes even fix the issue you run into yourself. Ofc this isn't necessary to drive a car, but it's a parallel progression imo, if you know more, you have an edge over people who don't 😎
Absolutely agreed Sethi! Especially if you drive the car in the middle of desert 😂. It’s indeed always good to know how to diagnose the issues and potentially fix them or know where to get help 🙌
I concur! I just ordered linear algebra and calculus books for refreshers this summer
I have to say that I really enjoyed the amount of content you put in this video. Thank you.
Oh so glad, I really appreciate it!! Thank you for watching 🙌
Awesome video Thu Vu! Your comments on the end of the vídeo about the impostor feeling and about the understanding vs explanation is just perfect! Ty for the amazing content.
Glad you enjoyed it! 🙌🏽 Yeah, the impostor feeling is so universal and hard to befriend. Glad you found it useful what I talked about 😇. Thank you for tuning in!
When I encounter new topics I don't note them 😢, that's why after a few days I forget those topics.
Thanks Thu Vu for marking the point , this video was great.
Haha I can totally relate to that, Swapnil! I forget to do it all the time 🙈, always learn the hard way. Thank you for watching!! 👋
Absolutely amazing. You have encouraged me to dive into data analytics. Thank you so much.
Great video Thu Vu, Thanks so much for the tips especially for beginner like me who is just getting into DS field.
You're very welcome! Glad it helped! Thank you for watching :)
awesome video as usual! majority of the maths are abstracted by libraries nowadays but fundamentals are very important to know which ones to use!
Thank you, Kevin! Really glad you enjoyed it! 🙌🏽 And yes, absolutely agreed with you about the libraries nowadays! I love them but still quite often had to dig into their documentation just to be sure what they actually do 😅
Thanks Thu! I really enjoy your videos! Thanks for sharing your experience!
Glad you enjoy it! Thanks for watching 🙌🏽
Thank you for the wonderful video. Although I have learned most of the Math you mentioned in my electronic engineering course, the video is still very interesting and helpful.
You go girl! I love your channel. Thank you SO much for making it. Its great to see other smart women. Again thank you and do your thing! Keep the videos coming 🙂
You are so welcome! Thank you for these kind words, it really means a lot! 🙌🏽
Thanks for the great explanation!
I found that very helpful and insightful!
Keep up the great work!
And, Good day!
Recently found your channel - GREAT STUFF. Thanks foe sharing your knowledge
Can you please share the one note notebook with the MIT notes?
That what I hope 🙏
Yes please
Thank you for making this!
Hello!
So this is my second watch on your channel and I must say you make really good content.
Data Science is too much for me so I learn mainly for Data Analysis. I want to learn Mathematics for Data Analysis. Nowadays most of my learning constitute Statistical Analysis and some probability related parts. I am learning it in R from a book. I started to get interest in the beginning but after coming across different testing methods like ANOVA etc. it started feeling boring 😅
personally I was weak in mathematics during my school time and sometimes it feels like I am taking a wrong way by going towards analytics haha...like at some point of my career journey mathematical nightmares will haunt me lol
Hi Vivek, thank you so much! I can relate to the feeling of getting bored when learning too many statistical testing methods (that I'd probably never use)! I'd say it's okay to rotate among a few different topics and come back to this topic later, maybe you'll then feel more excited to learn it 🤓
Thanks I loved this video. Thanks for recommending those R books, they look very well.
Glad you liked the books. Thanks for watching Angel!
Calculas is hardest when you enter integration part! rest are super easy, like Limits, Derivatives & It's chain rule and Partial derivatives!
This is a great video, I think a lot of people are scared of statistics until they start to need them, or use them in ways that are relevant for their own data.
Totally agreed! Math is indeed a bit scary but it's also so powerful!
Brilliant videos, one can feel the passion in your words
Thank you so much for your kind comments 💜
The first video I watched on your channel Already Subscribed👍👍👍
Yaaaay!! Welcome to the club! 🙌
I learned maths for data science but now may leave data science for maths.
Maths is so much fun and powerful.
That’s an interesting switch! Great to hear you found your ‘true love’ 🙌😁
Thank you so much for your usefult guidance. Hope you can extend your channel and wide spread the your inspire along data to everyone, from a developer in Vietnam
Thank you so much for your kind words Quang!! 🤗🙌
@@Thuvu5 Hope I can study more from you, you're very kind, thank you.:) :) :)
Well it really depends on what you want to do with data science. If are in research then you probably need more maths than coding skills. There is crazy tensor algebra if you want to modify the reverse AD without using torch.autograd.
Chị Thu Vũ chính là người dẫn em vào con đường "nghiện ngập" học data science này.
Wow that Bellman dating equation is next level! Can you make one that covers when to give your spouse flowers? 😃
Very courageous the way to present your ideas and recommendations and specially you experiences to encourage people!. Excellent content, very wise. Congratulations! I'm sharing you videos with my son's who are going to school. How immensely wrong were the people that put you down when younger. She on them.
Awesome Video Thu Vu! Thanks for the tips!
I think that a good resource for statistics learning with python is the book Practical Statistics for Data Scientists by Peter Bruce, it presents the essential knowledge with applications in python and R as well.
Thank you for the book recommendation, Joao!! Oh it seems like a very good book, it actually popped up sometimes on my Amazon page and I didn't pay attention. Awesome! I'll check it out! 👋
Hii!!! I find your content extremely helpful and thank you for the awesome videos so far.
Hey Yyothi, thanks so much for this!! 💙
Another Great and Useful Video from the Great Thu, Thanks , Love your videos
Aw thanks so much for this!! 💛 Hope you're doing well.
You're looking more healthy, I'm happy for you. And great video btw!
Thank you so much! 😄 Yes, I've been feeling much better after that horrible flu 🙈. Thank you for watching!
03:51 made me laugh so hard. Thanks for the video. Also , can (and how do) we get access to yours and Stavros's Notion pages?
Love your video,em. :) Thanks for sharing your opinion
Youre not wrong. Theoretical Math, Physics, Chemistry and Engineering are wayy harder than programming because youre discovering/inventing the science wile trying to solve daily tech problems. Programmer dont understand this.
awesome informative video
also need to know the geometry and trigonometry
My biggest issue is retaining what I learned, can anyone suggest apps or platforms that help you record what you learned?
This is why engineers and physics majors are the best poised for DS. They been dealing with heavy math all their life.
Haha absolutely!! Unfair advantage 😉
You can say that again Chac 😁✨...all our life!
@@FaruqAtilola I am a EE grad who left engineering and quantitative work many years ago. I go back to school to do a masters in DS and I feel right at home with the math. DS students often ask, how much math do you need to know for DS? My response is, you need to know just a little more than your competition, but your competition will often be engineers.
Thank you for poping into my feed and give me an anxiety strike… but seriously, great video, I do recommend the MIT open course, they have a great selection of courseworks
Haha great to hear! Hope it didn’t make you too anxious 😂. And thanks for the recommendation! 🙌
dive into deep learning is a great book for concept+code + math's behind the concept and it's free
Thanks a lot for sharing, Arun!!
Informative, professional and entertaining, especially sadistics, had me rolling lmao
Hi Thu Vu! Just started watching your videos and found peace on them, I just graduated six months ago from a BsC on Financial Engineering, focused on Data Science and found my passion on ML. It is overwhelming wanting to know everything sometimes, but now I am taking one step at a time. I started working on a fintech startup but being the only DS Engineer over there is making the journey lonely. Even if I am expanding my portfolio and doing a lot of interesting courses I want to know if you (or anybody) have any recommendations on communities or "social networks" for expanding my DS network and getting interaction, rather than just following big names on LinkedIn, as of now I consider myself a student. Greetings from México!
Hey Fernando, I can relate to the lonely feeling you're experiencing. think there are a lot of communities out there. I used to join local Data science Meetups in Amsterdam to meet and talk to people. Online there are also a lot of Discord communities (for example Tina Huang has one of her own). Greetings from the Netherlands! 👋
Another great video. Thanks Thu Vu. One question: could you reshare stavros vogiatzis’s notes? Thanks again!
I’m afraid I need permission from Stavros to share it. Also it’s a paid course so in a sense, it’s not advisable to share it freely on the internet. But I hope Stavros will update us soon about this in the pinned comment 🙂
@@Thuvu5 totally understand. Thanks again:)
Thank you for the video 😊
When I need to find some pattern in our data, I always remember what Einstein said, E = mc2 ! :P
Haha you totally got this!! 😉👋
Thanks a lot for the video! Is mit applied data science notebook available to check out?
Love your video style, Do you edit all of your videos by yourself? If yes what software do you use?
Thank you! Yes I edit videos by myself (but currently looking for a video editor to help me with this). I use Final Cut Pro 😊
A neat & helpful channel!
9:11 - How to make such nice one note docs...any links please
ICL prof cert in A.I & M.L was a complete waste of money. I spent £4000 and thankfully got it refunded halfway through. Thanks for the vids really enjoying your content
Mam i do follow you on linkedin as well and you are really doing great thank you ❤
Stats is a weird one. _Probability_ is definitely mathematical, since Kolmogorov's formulation is basically just a normed measure of event space. Also LLN, the properties of the distributions and their relation to eachother, statistical moments of sampled data formulas are all a priori. Bayes factor maybe, but that's not so much empirical, it's more just a matter of judgement when to use it.
Bro , you are flirting.
@@siliconewall_e Hah, I wish! The inductive sciences just have this kind of fascinating estrangement that I'm interested in.
@@Eta_Carinae__ i know , i was joking 😁
Thank you, Vu!
I agree that there are many things we studied at college may not be useful in real world settings. But as a student, it is a good training process by taking hard core subjects to build up a sophisticated brain 🧠😁
Totally agreed! 🙌
Hi Thu!,
I would appreciate it if you share the notebook system, please
thanks so much. Really good tips for learning
is there a way to learn the Starvros Vogiatzis system??
How can you come from computer science background and not know what eigenvector and eigenvalues are?
Highly appreciate for your efforts Thu Vu.Could you please recommend any book to start for DS jouney for a beginner specially from scratch!!
Great video. Thank you!!!
do you mind sharing link to your notion notes
Completely fell in love with your videos :) Cheers from Pakistan.
Aw thank you so much for this! 😇 So glad you liked them!!
wonderfully helpful! Thank you!
So glad! Thanks for tuning in 🙌🏽
Could you make a video about the art and best practices in reading documentations:
1] for data to understand it.
2] for python
Thanks :-)
great stuff, thanks. how did you get the graphs to be animated?
I don’t do the animation myself so I can’t tell you 😅
This video help me a lot!!!
Thanks for the tips
You, and I mean everyone of you hopefully reading this comment, must use every single algorithm or mathematical concept on a particular problem within a particular context. So if you want to learn calculus/backpropagation/naive Bayes classifiers etc then define yourself a problem or search for a problem were the algorithm you want to understand already used. Then search for an already got documented and commented jupyter notebook and go for it step by step and do your notes. I also recommend TorchStudio to see what happens with your data on detail and what training parameters really do with your tensors. Ok, my tips tend to be a little bit machine learning-ish but whatever. If you try to learn something without context in this field you will end in a big frustration with math. Just my 2 cents.
great video brilliant summary
Thank you Thomas! 🤩
Thanks for this amazing video. 🇮🇳
Thanks a lot
I believe you had skipped couple of mathematical concepts like Manhattan Distance, SVD, etc ... Math is much needed for Machine Learning if not for "Applied Machine Learning". Coursera course Algebra for Engineers from Hong Kong University (the same is available on TH-cam) helped me to basic mathematics...
Great video, thank you for the tips
I have 5 years of experience in mechanical for can I go for Master in data science
i actually quite like maths (especially statistics and probability)
I really enjoy your videos Thu! Very insightful you latest one! I was always wondering how much Python should one need to know for an entry level data analyst position.
Someone should know Python at intermediate or advanced level ... of course the more the better but are there really any minimum requirements?
Will it be helpful for his/her role to know OOP with Python and advanced data structures (i.e. stacks, queues and linked lists)?
Hey there, thanks! For an entry level data analyst position I think an intermediate Python level should be ok. OOP and advanced data structures might not be necessary, unless you are doing really intensive programming stuff in your job, like building applications or data engineering
This part is hard for me right now in my data science course… 😅