👩🏻‍💻 Why Macbook M1 Pro is the BEST laptop for Data Science

[@DataProfessor]

Certainly agreed that the digital notes are amazing as are the YT studio setup, love the lighting, just curious if you're using a Light dome softbox.

[@LukeBarousse]

I'm curious about this as well!?

[@Thuvu5]

Oh thank you! Glad it looks a bit nice haha 🙌. I’m still using a regular photography softbox but planning to switch to the more light dome with dimmable light soon. I find that now sometimes the light is too bright on my face. Thanks for watching, Chanin! 😀

[@DataProfessor]

@@Thuvu5 Thanks Thu Vu for the insights 😊

[@THE.MICHAEL.ANGELO]

That breakdown starting at 3:38 is flawless and [for me] the way it was explained somehow made sense of what I've been trying to learn for the past year!!! WOW! Thank you!

[@Thuvu5]

So glad it helped! Thanks for watching 🙌😄

[@LukeBarousse]

I am so jealous of your neat and organized digital note-taking ability!! 🙌🏼The notes I take look like a hot mess 😂🤦🏼‍♂ Also, so glad to finally get to hear your thought on the M1!! Such a powerful computer

[@FaruqAtilola]

Yeah, I must say, the organisation is quite commendable ✨ And I really like this connection between you two; featuring in each other's upload 😊

[@Thuvu5]

Haha thanks, Luke! Honestly I only showed the most decent notes I made 😂, some others are like a mess as well. I was so pumped up about this M1 Pro by some of your earlier videos, am really happy with this!

[@LukeBarousse]

@@FaruqAtilola Teamwork makes the Dreamwork!! 🙌🏼

[@LukeBarousse]

@@Thuvu5 Thats good to know that I'mnot the only one talking those kind of notes 😁 And heck yeah, this video came out so well!

[@Thuvu5]

@@LukeBarousse Haha no you're good. Or we can one day share our worst notes of all time and see who wins 🤣

[@Po0pypoopy]

Can you do a video on the kind of lifestyle to expect as a data scientist or analyst? Are you always working overtime? How frequent do you have to make diagrams …. What about coding …any coding involved ? Is it a relatively stressful lifestyle ?

[@Thuvu5]

Hey Yessi, I’ll probably answer this in the Q&A. Thanks for suggestion 😄

[@iamsarahmchenry]

Exact explanation I’ve been looking for… for years 🎉

[@baoung9032]

Thank you very much for the courses on DS, it's a huge help! Keep up the good work!

[@Thuvu5]

Thank you!! Really appreciated it 🙏

[@sriram-xp5sg]

Thanks for the recommendation sista...loving the new macbook. I am currently using the same model shown in the video. Truly an amazing laptop

[@Laura_Bass_]

This was very useful in deciding what laptop I should buy….

[@andrewgould3690]

I would appreciate a follow up video on this topic that shows how you installed R and Python on your MacBook. Are you using the version of Python that came with the laptop? What do you use for an IDE? What other applications did you install on your Mac that were related to data analysis? Additional guidance would be much appreciated. Thank you.

[@bakhtiyor_sulaymonov]

Thanks for the video I was looking for )

[@freedman1405]

love seeing your content gaining more traction! been your viewer ever since. good job! :)

[@Thuvu5]

I’m so happy to hear you’ve been following my content! Thanks so much Freedman!! 👋😇

[@l1k2j3h400]

Nice review Thu. I really would like to look for more practice about the system (hard/soft) setup as a data consultant role :) that's seem to be a right path for my data journey.

[@petersultan6251]

I just really want to tell you how much I appreciate your help😁😁😁😁

[@kiraqueen0]

Its actually a really good choice. It has that enormous memory speeds and uniform memory access. Plus, some libraries support acceleration on Apple GPUs. However, your best bet would be to build a decent PC. Even RTX 3060 would be a good choice for a starting package. The best thing which mose people tend to overlook is that with the PC, you get a chance to upgrade your hardware part by part instead of buying a whole new laptop once it gets slow or old. With AMD sockets its even better. You can like jump several generations without having to swap a motherboard. Lots of cheap storage with old HDDs and multiple SATA ports is especially good when working with very large datasets. Its something hard to find in a laptop if possible at all.

[@Thuvu5]

Thank you for sharing Edvard! Totally agree that it’s a big plus with PC to be able to upgrade the hardware 🙌.

[@juliansanchez9530]

Correct me if I’m wrong, but I think the point of the video was to recommend a portable laptop. I don’t think anyone doubts that building a desktop pc is the best choice overall 👍🏼 you’re absolutely right though

[@musashi4856]

“Geek Alert” is a better description than “Nerd Alert”.

[@waynelast1685]

Please talk next about using the cloud for data analysis... WHY, WHEN, HOW, WHERE, etc. Subd your channel. Thanks for the good info.

[@mehdismaeili3743]

thanks for this video.

[@j900270]

Your explanation is so good and on point, give me a clear idea on how the hardware works! Thankyou:D

[@Thuvu5]

So glad it helped!! Thanks so much for your kind words, Yuning!

[@blaketownes6746]

Love the content! Would you share any wisdom you have learned from data cleaning/prep? Do you have a process you follow? Also, any tips on how to learn data skills/concepts faster?

[@Thuvu5]

Hey Blake! Data cleaning is indeed a very good topic to cover! I’ve had it in my list for so long, really need to put my head down and work on it 😄. Thanks for the suggestion!! And I do think working on projects and practice is the fastest way to learn data skills and concepts

[@paco3447]

Sorry, but PC with Nvidia CUDA is the way to go, specially for model training. Is there any workaround in order to use TF with native Metal support? Yes, but it’s quite limited and a mess. And vast majority of already available libs (neuroscience, imaging, etc.) are CUDA based (and no interest to be ported anytime soon, at all)

[@Chuukwudi]

Personally, I do not think mac is a good idea for data scientists. Popular machine learning libraries like Keras, TensorFlow and PyTorch are more highly optimised for NVIDIA hardware due to CUDA and CUDNN capabilities. This is not present in mac. Linux is my best bet as it gives me control and allows me to manage my precious limited resources.

[@jatoday]

I think this is true except if you will be utilizing cloud computing resources for GPU optimization.

[@abusalem411]

Libs are optimised for Apple Silicon, thus can utilise it's GPU.

[@robinfelix3879]

Hi, Did TensorFlow and TFX (extended) worked on Mac m1?

[@olganerd]

tensorflow works on macos 13 and you can use it with jupyter notebook. if you want to try it out I can send you a link on how to set it up and run popular benchmarks.cheers!

[@Photon1345]

Speed can be a misleading/very casual term in terms of physics and technology as it could mean many things. However, bandwidth in COA refers to the amount of modulated data that can transfer through the channel every second. Bandwidth can have different interpretations in different domains but it always refers to a range of quantitative values with a minimum limit (f_low) and a maximum limit (f_high) and the relation is Bandwidth = (f_high) - (f_low)

[@KaraboMoremi]

13K subscribers in 31 videos. I'm so proud of you🥺

[@Thuvu5]

It’s been a ride, Karabo 🙌. Thank you so much for supporting the channel 🤗

[@KaraboMoremi]

@@Thuvu5 I will be starting mine soon. Just completing a Data Science certificate on Coursera now

[@jhoon6227]

Great video!

[@trarihamza7047]

Great choice , but unfortunately we cannot run power bi on mac

[@fernandourrutia2566]

This is a very good video !! 🔥❤

[@abheykalia3409]

Another thing, M1 chip contains CPU, GPU, RAM and other components in a integrated form i.e. in a system on chip, which doesn't require the components to copy the data between one another in order to access it, since they can utilise the unified memory architecture, and also M1 is based on Arm asm lang, which Apple might have modified upon to build a much more efficient system. Plz correct me if I'm wrong

[@Thuvu5]

Thanks for sharing Abhey! Yeah this is quite interesting. Yes I think that’s roughly correct, I understand the same that system on chip design has everything on a chip and CPUs share memories and so they don’t have to copy data all that much. But of course I’m not a computer engineer to tell more about this 😅

[@Photon1345]

Even SoC are based on Von Neumann architecture, the data has to go to the memory i.e. outside the processing unit and thus there will be a fetch time. Even in SoC organisation there is CPU, GPU, DRAMs, Cache memory, Controllers. Thus any instruction execution will include copying of data from the memory units into the processing units. What SoC does it minimise the physical distance between the components which in turn minimises the fetch time as the data transfer time depends on the length of the conductor and the propagation velocity of the electric field along the channels. M1’s are not the first SoC chips that came in the market… it dates back to 1970s. Apple had been using SoC for a while now.

[@anmoldwivedi7205]

Question - What do you do when you have to work with proprietary software on windows like - Power BI or Excel or Tableau??

[@umayerreza]

They use VM then 🤣🤣🤣

[@dustinallen5586]

You don't think that its best for a data analyst to use a windows laptop? In my career we use Alteryx which can only run on Windows

[@Dee14444]

Timing! I am shopping for a new laptop as mine is outdated for datascience. I have been thinking of mac vs win 10. How good do you think m1 pro will run for the next 5-6 years for one's datascience needs ?

[@Thuvu5]

Hey Dipannita! I think it’s quite subjective as everyone probably has different time horizons when it comes to changing tech gear but I personally think I can see myself using this laptop for the next 5 years. Hope you’ll find your favorite laptop to buy soon! 😄

[@myrajamian9766]

this is the video that i need. tq for explain in very details. i really need to decide which device should i choose. ios or windows. tqqqq

[@uttonio]

omg I just know about this. I own this laptop and do some basic code running on R and have no idea how powerful it is. Thanks chị nhiều ^_^

[@TheMISBlog]

Great Video Thu, Indeed t his Laptop is really good for Data Science and Video editing,wish you all the best

[@Thuvu5]

Yay! thank you! I love it as well 😄

[@elenBk]

Hello! Any recommendation for those that prefer windows/linux laptops? 😊

[@mikeylejan8849]

Gaming laptops are also good with data analytics

[@benjcheah3031]

I wish i had you as my teacher when i was 10 years old...for 10 years...*sigh...

[@lesliechiang1710]

Can't be... the memory is not upgrade-able cheaply. In my opinion, is better off to have Linux on your previous machine.

[@abhisheksinghmahra446]

MacBook air for student who is learning data science??? Will it be a good option or I should go with gaming beast laptops of dell hp etc... 😭 Please reply

[@Thuvu5]

Hey Abhishek, MacBook Air is a good deal for DS students, but on the other hand for the same price you might find a Dell or HP or Lenovo laptop with better specs. Check out and compare all the specs that I mentioned in the video, hopefully it will help you make a decision! Gaming laptops generally have better GPU, meaning it is faster for graphics and floating point calculation (eg deep learning). But really up to you if those are of importance. I’ve heard Dell XPS is a good laptop, so check it out and compare a few of those from different brands. Good luck! 😊

[@SantoRedentor]

I have this laptop from my company. I hate the 14 inch screen with all my heart. I know some people can, but I definitely need a bigger screen. Which basically means that I cannot use the computer on its own. Which makes it lose the point of being a laptop in the first place. Having the 16 inch version would have made a world of difference as I am happy with the performance otherwise, but my company refused to provide me a bigger one. I also don't like MacOS coming from a Windows. I'll admit that the computer has given me less problems than a Windows would have up to this point, but at the expense of being very limited in how you can do things. Overall I think that the hardware and construction is the best (I have a Dell XPS17 personal laptop and the MacBook Pro feels better in every way). Design wise the new MacBook Pros are uglier than the last generation, but at least these ones handle the heat much better. My laptop barely gets hot, while I literally got burnt from touching my wife's MacBook Pro 16 2019 or 2020, after she had been taxing the computer with... A Zoom call. I can recommend this computer but I'd make sure that you choose the right size for your screen space/ portability needs. In my case I got the short stick because I (and my eyes) care a lot about screen space and I don't care the least about portability or weight, which makes it miserable for me to use this computer without it being plugged to an external screen.

[@kevindeloria2920]

Haha just went through that yelp dataset for my big data course. Ran it in coursera's shell and it took ages. (especially when you start merging user, reviews, and business)

[@Thuvu5]

Haha yeah it does! 😅 I found someone online merging the data in 5 batches, so I used that approach as well. Much faster!

[@chillymanny714]

Hi you did a great job! I was wondering if you could speak to how R can use all cores because I’ve read you need to use a special package to access more cores in the program but I’m new to R and parallel computing.

[@Thuvu5]

I think the 'parallel' package in R is what you're looking for. I use this package to speed up the code in some projects www.r-bloggers.com/2017/10/running-r-code-in-parallel/

[@dbk1150]

thanks for your video, how do you use excel for data analysis? Thank you

[@humayunkabir-jl9tj]

Thanks

[@chadleever492]

What about keyboard shortcuts with the small keyboard? I have a MacBook Pro, but I use a wireless full-sized keyboard with it so that the shortcuts will work properly.

[@uminhtetoo]

Thank you so much for sharing.

[@duchien-hisus]

Chị làm 1 video clip làm rõ hơn về DE/DA/DS đi ạ. Xem các youtuber nước ngoài xong đối chiếu ở VietNam thì mơ hồ quá. Em cảm ơn chị

[@valchaneco]

Hi, Thu. Would you still recommend the same specs today? I’m considering getting the mac mini m2 with 16gb unified memory and 512gb storage, 8 core CPU and 10 core GPU. Would 24gb unified memory be better? Hoping to hear from you. Thank you.

[@Photon1345]

Nah… I mean you can keep flooding your CPU with extra memory and it won’t hurt but going over 16gb on most of the personal computers is just wasting money for extra resources you are never going to use. If you want to run a full workstation for DS, I suggest use cloud solution… deploy your clusters there because consistently pushing your CPU and GPU for long training sessions is not going to be good for your personal computer. Mac is generally really good in terms of memory management so don’t worry about hitting limits anytime soon. I am a CSE student and daily driving my Macbook Pro M2 Pro 14 inch with 16gb RAM and 512 gb SSD, constantly using CAD softwares, Matlab, Python, Java and many other industry grade software’s and I never saw a single shudder. P.S. If you really want to put in extra money then definitely upgrade your RAM, not the SSD because u can find external storage solutions but same is not true for the primary memory.

[@christopherhall1216]

I'm currently not an Apple user. Do you have an alternate suggestion?

[@ThisAintIt435]

Really torn between this and the 16inch

[@neonxumalo3647]

I bought this computer as I’m preparing to begin my masters in data science this fall so it’s nice to know I made a good choice. Thank you for this.

[@adriacometmartinez]

Great video Thu! Thank you for your insights on this laptop, they really came in handy for me. I'm currently looking for a new computer to practice data analytics since the one I have is about to die. 😅 Keep it up! 🤙

[@Thuvu5]

Glad to hear, Adria!! 😃🙌 Haha good timing then! Hope youI’ll reach a decision about what to buy soon! Thank you for watching ☺️

[@adriacometmartinez]

@@Thuvu5 I actually had already seen other reviews, but after watching yours specifically for data analytics and data science I decided to go for this one! :D

[@FaruqAtilola]

Hello Thu Van, Thank you for the review. This channel deserves more attention than it's getting really! For the Q/A: As a newbie, I would like to know how you handled impostor syndrome starting your career as a junior data analyst.

[@Thuvu5]

Hey Faruq, thanks for such kind words! 😇 That’s a very good question, I’ll put it in my list 🙌

[@JohnLuthieArcillas]

Hi Thu Vu… nice content… on your experience using M1, how about the app flexibilities of other apps compared to window PC?

[@deeek92]

Very detailed video. Thanks for this :) I have a query - How much battery backup do you get WHEN you plug your Macbook pro to an external monitor? My intel core i9 macbook pro 16 just runs for about an hour when I connect an external monitor .. Sad! :(

[@yujiitadori225]

My final goal is to become a Data Scientist, but the initial goal is to get a job in Data Analytics so which laptop will be ideal for me in the 1400 dollar budget!

[@naveenrs7742]

Why can't you build your own storage server?

[@khaledboud146]

Thank you for the video it's so informative. Also it's made me remember my 4 GB pc who is super slow 🤣🤣🤣

[@Thuvu5]

Haha those good old days 🤣. I remember when I was small seeing my dad buying a bunch of RAMs to add to the old pc in my house and didn’t understand why. Thanks for tuning in, Khaled!! 👋

[@khaledboud146]

@@Thuvu5 I have question about using numpy library to make the code running faster in python. Is that effecting the data or not? For example converting data from int64 to int8.

[@Rocky-wt8lz]

Great vid! Currently use the 2020 M1 Mac Mini as a workstation and was really good value for entry data science as well. Noticed you said you use R, now I'm curious, how often do you use R and also do you have any experience with Bayesian learning (STAN or something else)

[@MarieNGUYEN-c4k]

Hi Thu, I heard that Macbooks cannot run PowerBi , what is your thought on this?

[@Thuvu5]

Yeah that’s true. But you can use Parallel to run a Windows os system on MacBook. It’s pretty easy to set up, but does cost money

[@Matlockization]

Yeah but Apple is 3X as expensive. I wonder if you got a gaming laptop would the results be better ?

[@yj_1128]

I‘m also working on data analysis using Python. Looks like a really good review☺️ I'm currently using a laptop with 11th generation i5 cpu and 16gb RAM. I really want to use Apple silicon, so I'm going to buy an m2 pro MacBook. 1) 10 core(6 performance+4 efficency), 32gb ram m2 pro 2) 12 core(8 performance+4 efficency), 16gb ram m2 pro If you choose one of the two options, which one do you think is better from the perspective of a data analyst?

[@Thuvu5]

I’m actually not sure about this, looks like there’s a trade off you have there between RAM and cpu speed. But if I have to choose I’d probably get the 32gb

[@Photon1345]

Its a no brainier. Go for RAM. For Python only, I would say… don’t even bother… it’s efficiency is usually less about the silicon but about the level of optimisation. More cores = more parallel processes but also means more heat and throttle and the gain you will have over the other chip will be minuscule. Over that if your process if badly optimised, forget even that. Python carry lots of overhead and I hate it for that. I think your traditional python packages run via Rosetta and makes it slow… there are different binaries available for ARM processors that needs some extra effort to get running and utilise the processor efficiently.

[@thamimmo]

Hi Vu, which bi tool is a better option for beginners

[@jasonsykes4199]

I use GPU's for machine learning.

[@shivamvishwakarma4377]

can you use powerbi desktop? without parallels?

[@ecommercewithjay8857]

i plan to buy mac mini m1 for python, pandas, numpy and learning about AI development with python and data science. Do you think mac mini m1 is good for beginners learning? Great video and will like the video.

[@Thuvu5]

Yes, definitely. I think it should do the job!

[@ecommercewithjay8857]

@@Thuvu5 awesome. thank you for the feedback!

[@gz3395]

Hey Thu! Now with M2 released what laptop would you recommend for data analytics? M1 or M2? I'm going to retire my old macbook pro (2009) and I want a reliable alternative as an entry-level data analyst. Cheers

[@Thuvu5]

I haven’t looked too much into M2 but I think the bit extra performance of M2 is probably not noticeable in most cases. I think M1 is a reasonably good option already, but if budget allows, go for the newest tech 😏

[@darkmemes7487]

Hello Mam, i am new to data science and started learning it, i was considering the Apple Laptops but got to know that Power BI is not supported on MAC OS, Do we have any Way through for this?

[@Thuvu5]

Hey, thanks for the question! It’s indeed a bit of a hassle that PowerBI is not supported on MacBooks. BUT you can use Parallels to install Windows and PowerBI on your laptop. I think this tutorial is what you need m.kzbin.info/www/bejne/qGmcl3qFgpaVp5I

[@beyonder7817]

what about base model m1 air 2020

[@oskarbarrera1420]

hello, I really loved your video, I have a question, I am a computer sciences master degree student and I am taking courses like machine learning, deep learning and artificial intelligent, do you recommend the macbook air M1 or should I go for a pro or promax? I need it for my studies. thank you very much for your help.

[@fruitfcker5351]

02:09 I noticed you use chunks to read your data seat. Don't you need to concat/append them into a separate dataframe and work on that new dataframe?

[@michakozak3064]

Why did you choose 14" instead of 16"?

[@Thuvu5]

Hey Michal, it’s mostly because I’m small and don’t want to carry a big heavy laptop with me when traveling 🙈

[@tipstricksreviews4481]

I like the video. Apple seems made something good with this model finaly.

[@akin242002]

I have to respectfully disagree here. Dell XPS or Lenovo ThinkPad 14/16 are better for ML, especially if a person uses NVIDIA chips. Honorable mention to M1 MacBook Pro 14 without NVIDIA chips, AWS, and using Python.

[@ruelvaliente7265]

only problem is we cannot use Microsoft power BI

[@jujjuj7676]

I disagree, being that your into analytics and your very core is parsing data. I don't think you have enough data points to claim Macs are best for data science. I'm thinking the title should be more like "MACS are best for YOU in data science". The majority of really crafty tools are not made for Mac OS because most the serious data science developers tools are programmed in more flexible open source languages that allow you to tap a vast array if data from a wide variety oh open sources and Mac OS are restricted and not very inviting to data science developers ( Biomedical, Finance, Economics) You should spend more time testing out tools for data science in different fields. You will see the more powerful tools, scripts and apps are far from MAC centered, matter of fact id go so far to say own right scarce. But the ones the Macs do have do look pretty in the surface. I'll give it that, but id take function over design anyway. I don't have time for Mac preset limits and closed mentality or to even consider the bloated price, terrible update cycle etc etc..

[@sourabhsen5629]

Excel on mac?

[@BlacK201100]

Do you have any problems installing & running the data science libs like sklearn, xgboost, numpy, scipy, pandas...?

[@olganerd]

for the libs mentioned, it uses a cpu and it can be used in any mac. certain gpu libs like tensorflow will run only on macos ventura.

[@cisimon7]

Hello, is that pybullet simulation running on M1 mac? Been trying to install it with no progress

[@Thuvu5]

Yes it is. I remember I just installed it with pip with no problem.

[@cisimon7]

@@Thuvu5 No way, what did I do wrong. Thanks anyways, I will check again

[@txreal2]

So how much are you selling the old Windows laptop? :)

[@Thuvu5]

Haha I don’t have it anymore, unfortunately 🤣

[@hiepnguyenbg91]

Thu ơi, mình định mua Macbook pro 14 M2 pro để làm data analysis. Không biết có nên upgrade 32GB RAM không bạn nhỉ? Mình sợ thừa thãi, mà RAM cũng đắt nữa ^^

[@Thuvu5]

T nghĩ nếu làm data analysis với data không quá to thì 16gb là đủ. Nhưng nếu vừa train mô hình lại vừa muốn chạy nhiều thứ khác cùng lúc thì nhiều RAM hơn vẫn tốt hơn nhanh hơn, một chút thôi ah. Thi thoảng lắm laptop mình bị treo đều là do hết storage chứ k phải do RAM. Nếu dùng cloud services để train model to thì RAM cangf k quan trọng.

[@niharlathiya]

Is 16/18 GB RAM enough for data science/ machine learning and other programs simultaneously like tableau, sql, docker etc? Or should i spend extra for 32/36 GB ?

[@Thuvu5]

I think 16 Gb should be enough, but the more the better of course if the budget allows

[@niharlathiya]

@@Thuvu5 i see, thanks. And what about SSD? How is it working for your data science projects? Since I am also a data science student, just want to know should I get 1TB or getting 512+ external ssd or getting iCloud also works fine?

[@Thuvu5]

​@@niharlathiya mine is 512 gb and I use iCloud and 2 external SSD hard drives of 2 TB each haha. Bought them at discount and it was so worth it. If you need to store a lot of large data (videos in my case), I think using external SSDs are the best

[@niharlathiya]

Thanks @@Thuvu5 , this helps :)

[@JimCallahanOrlando]

I am still on an i7 notebook with Windows 10. Windows has PowerBI, but Mac has Final Cut Pro (important if video creator). I plan to use Apache Superset instead of PowerBi or Tableau. Any issues on Mac with email (such as GMail)? Curious about any minor software differences (keystrokes or UI) in going back and forth between Windows and Mac.

[@Thuvu5]

Hey Jim, so far I haven’t seen any differences in the software I use like Gmail, Tableau, etc. And Final Cut Pro is awesome. Switching back and forth between my work laptop (windows) and my MacBook does taking some time to get used to, especially keyboard (Cmd vs Ctrl) and the different file systems

[@nil-xo4ce]

are there any compatibility issues for the popular python libraries for data analytics/data science?

[@Thuvu5]

I haven't noticed any issues so far.. If there are any issues, there are always alternatives for Mac.

[@nil-xo4ce]

@@Thuvu5 thank you for sharing! :-)

[@serge2033]

cool video

[@rpmy]

How i can enroll with your different courses specially in data statistics and research?

[@rpmy]

Im very interested... How much? When? How?

[@Thuvu5]

Hey, which courses are you referring to?

[@rpmy]

@@Thuvu5 statistics?

[@timisa58]

This is silly. The best laptop for Data Science is not an over-priced MacBook! You may have a preference, as she does, but you do not need a MacBook. 🙄 I am an IT director for an Apple-dedicated institution and have been using Apple products for years in the work setting. I am normally Windows or Linux at home. Please. Macbooks look nice and have enough raw power, but so do non-Apple machines, cheaper, and don't have the limitations with graphics cards, etc. Buy a machine you can afford and has the specs you need.

[@Thuvu5]

Good advice, Richard! Indeed sometimes Windows machines are cheaper and have equivalent if not better specs overall. I’m just a sucker for Apple products so I’m totally biased 😅

[@GolbalEduVentures]

@@Thuvu5 you have too much money at hand 👏

[@adesolaawolesi7870]

Pls is 8gb ram laptop enough for a data scientist

[@valchaneco]

@@Thuvu5 Thank you for creating these videos. Which mac mini m2 would you recommend to someone who wants to be a data analyst and also edits videos?

[@venkatprasath01]

@@adesolaawolesi7870 no it is not I’m currently struggling with one! Please go with 16GB

[@quocphantruong]

I think 512 is not enough, should be at least 1TB minimum. If you could then go for 2TB

[@Thuvu5]

I thought so too at some point, but then I realized I can store things on the cloud instead. Suppose if I lost my laptop that wouldn’t case any issue 😜

[@mischievousachiever7896]

Okay, first commenter here hehe

[@Thuvu5]

Haha yay!! 🙌😄

[@thuylinhlinh1986]

Hi Thu, do you think it's worth spending an extra $400 for 32 GB? I'm studying data sciences, too, and I will work with big data next semester.

[@Thuvu5]

Hey Linh! I think it might be worth it if you need to do model training and demanding computation on your laptop. If money is not a problem, I’d say it’s worth it in the long run. But for me I’m totally fine with 16GB as well, haven’t seen any issues so far

[@thuylinhlinh1986]

@@Thuvu5 thank you. I will go with the 32 GB

[@krislernguyen7169]

Hi Thu, would the base model Macbook Air M1 (8gb Ram & 256gb Rom) be enough for our DA tasks? ps: as I’m about to switch from my old Windows lap to Mac devices (also career path from the old job)

[@Thuvu5]

I’d go for 16gb Ram if budget allows, with 8gb you might run into out of memory issues when you run code and have other apps running too

[@yujiitadori225]

2020 Apple MacBook Pro with Apple M1 Chip (13-inch, 8GB RAM, 512GB SSD Storage) will it work for ML and Deep Learning work ? my budget is $1400 any recommendation

[@benravenhill484]

go for the 16gb ram, 512gb ssd m1 macbook air instead. you can get one for about $1300 at most

[@lesliechiang1710]

Can it run nvidia card? Maybe you can use some slow free cloud compute or expensive fast cloud compute. 8GB ram can't do much...

[@JudgeFredd]

Macs M1 and M2 are far better than any Intel PC

[@jennytumay]

😍

[@d3v487]

Such a Cute girl and Cute explanation 😍. Now I'll grab a macbook air 😁

[@Thuvu5]

Thanks for your kind words!! 😄 MacBook Air is a good deal as well especially for a less intensive workload

[@pedrosantarita1262]

large datasets 5.4 Gb 🤣🤣🤣

[@Shabi_ul_Hassan]

Microsoft products not working well on Mac e.g. SQL and Power BI are problemmatic on Macs unfortunately.

[@jizhou749]

Oh my god, you drink water in front of your Macbook. What a rich girl.👍

[@CarlosGonzalez-ll6xx]

14 inches? thats just stupid

[@yun6717]

Hi Thu,

[@Thuvu5]

Hi Yun, thanks so much for letting me know! I didn’t even notice it myself 😅. I’ve hidden it 🙌

[@siddhantdeepful]

The other reason is that the only windows laptop that has Apple level of work/corporate penetration is Dell and Dell laptops are pieces of hot garbage