Hi, could you kindly help me out with this? my OKX wallet contains USDT TRX20, and I have the recovery phrase (clean party soccer advance audit clean evil finish tonight involve whip action). How do I transfer it to EXMO?
This is great advice. Coming from someone working in ML and Robotics since 2018. No BS, to the point advice. This is the only ML learning advice video you should watch.
Hi since you did your BE in electrical with a specialization in robotics can you please suggest how learned robotics it will be really helpful as i am also currently doing electrical engineering and want to go into robotics
@@AdilSayyed-u5k Just have the skills, do projects and showcase them in your portfolio, and prep for interview, find jobs online like in Linkedin and Indeed etc. You will be good. In sha Allah.
That last part about building off tutorials is very real. I find that most of the youtube guides/tutorials are very basic and meant for beginners, but if you take something basic and implement your own ideas it can become a larger and larger project which helps a ton
This video is fantastic, I started learning ML recently and planed to build my first projects in 2025. The whole video was as if my mind was being spoken out loud as this is exactly how I was planing on doing. This reinsures me. I have a solid math background but always hated statistics. This Khan Academy resource will be soooo helphul. Great video, thank you !
Bhai solid math background btaana compulsory tha, ap to phr Jo week hn math mein un ko demoralize kr rhy hn, is field mein Mt aiye ga, mjy itni mushkil ho rhi hai, tumhaara kiye bny ga, khyal krein Bhai
Stats is super cool if you are looking to draw meaningful conclusions from the math that is done, and relate that to a problem and possible implementations. It's pivotal to empirical research. Once you understand that most of it is understanding data through cleaning it up and looking at it multiple ways - as seen in the common algorithms in 17 minutes video - you have most of the conceptualization down in your imagination. That is most of stats right there, outside of understanding the validity of constructs and methods, as well as their relevancy to fitting the data for interpretability purposes. You will love it soon. It's not extremely difficult, but it is insightful if you constantly keep in mind what it is showing you as you describe the data through the lens of statistics.
My goodness, if anyone wants to really get into ML this video is IT! Note: Not for people who say they want to do ML, but in reality just like planning what they will do. (Note to self as well 😅)
@@crazyparrot2786 some people just like planning what they want to do but never actually implement the plan. I think they meant to say that this video is not for these people, it's for people who actually want to do ML for real.
the hardest thing about programming and in general these topics is that it is not straight forward and you know what you need to learn. that is the hard part because then it takes a lot of time and gets boring really fast. nice video
This video is all i needed. I've been into Data Science for over a year now and i have done and learned many of the things mentioned on the video, but at some point i felt like i missed something on my way, and this videos had the answers i was looking for. Such a fantastic road map for ML
After going thru many tutorials and introductory videos finally found this one which is to the point and no nonsense. It gave great clarity on the overall journey unlike others who mostly confuses. Great stuff man. I'm definitely going to follow this.
Great content and giving the comments of ppl, who apparently are from the field, I definitively will subscribe! I just finished my DS bootcamp, and right at the beginning I knew it was an illusion, I would be able to master the whole thing in 3-4 months (even if I am ok at statistics and math). BUT, the 4 months gave me a good overview of the whole. Now, I am going back and started again to recap and practice, starting with python and dataviz.
I clicked on this video because im interested in the topic and not necessarily doing ML studies right now, however i am very much a beginner in coding and programming literally started my journey 3 days ago and proud to say i have written my first short code from scratch during my exercises, not sure if this is common in people in this field i just know a lot quite in later after few weeks the videos in this channel and other useful channels help keep me motivated and excited to keep learning i am finally pursuing what i love and hope you blessed reader as well.
This video is incredible, your entire channel is an absolute gold mine and will serve as an amazing resource for learners like myself and the industry as a whole! Thank you so much for your efforts
From someone that has (maybe) the majority of the math knowledge that you talked about, I can't emphasize on the importance of the python libraries that you talked about Pandas, Numpy and sklearn, we sometimes forget how important they are especially if you come from a theory based background. Also, If you have some knowledge gaps (especially in the hypothesis tests in stats) you'll have a big trouble trying to make good predictions and/or insights. Also, I want to make a point on the part when you talked about calculus, I think it's important to study not only derivatives of single variable function, but also for multivariable ones, because it's important , for example to understand from where the estimators formulas in multiple linear regression came from. Good advice.
This video pretty much covers A LARGE amount of a Data Science bootcamp I went through recently, very accurate step by step on how the content was made for us. To add, the VARIETY of jobs you can apply for just from these skills alone. Great video IMHO!
Grateful for the video brother, You just saved me hours of banging my head against the wall of youtube creator claiming to build a roadmap for ML and tell BS. Thanks again😭
Very nice video, you basically summed up what I do as a master data science student. Seeing it all presented in a video, I have realized how much I have learnt already.
Thank you. Im sure this will be just another comment and sink down, but still I thanks you for this. Many people dont know the milestones in learning anything. You provide it really good. Perfect.
Thank you for sharing the cleanest ML roadmap in such a beautiful video. I really appreciate your guiding and helping others. The video description contains all the useful links, which is a bonus.
After watching this amazing video, I have checked out multiple other videos on your channel. The content you and your team made is incredibly invaluable to the industry. Keep up the great work and the channel will grow exponentially. Thank you for the knowledge.
This is such a great video! So much really good advice squeezed into a 15 minute video. It almost feels unfair that this is freely available. Now I have to actually implement the advice...
also, don't go into ML (or data science in general) if you're just intrested in results. If you want to make the next big ai business, go to business and leave the code alone. If you want to add AI to your projects, learn fine tuning and prompting properly. If you like math and looking at numbers change, go to data science. If you're a data scientist (or on the path towards data science) try out making your own model, it's a really fun project
Great info ...gives the much needed confidence!!thankyou ....one request also ...what if some suggestions for interview prep (aptitude/behaviourQ's/situational questions)
This is the best motivational video and roadmap i came across. You assured me i am on the right path. ;))) I work in aviation, but as a cabincrew, i dont have much access to databases and if i did it would be illegal anyway XD as a person who is into ML for long time do You have any sugestions about what data i can use and where i can find some aviation enthusiast to colaborate on data analysis projects?
i learned ML, along with time series, recommendation system with help of mythical indian TH-camrs like campusX and krish naik in 5 months ... now I'm also learning MLOPS with azure ... in span of 1 year I learned ML,DL,NLP,cloud,MLops,SQL,pyspark,hive etc ... indian community has best teacher for ML,DL and now I'm an intern at MNC ...
One thing I would suggest from my son's experience of learning ML is, no matter from where you are learning. But, always try to focus on the platform which provides hands-on learning. For instance, my son learnt ML from Moonpreneur where he was provided with hands-on learning experience along with theoretical knowledge.
i am currently learning nlp and transformer have a quite depth understanding of this i think i need to study more research paper to get into this field
This video is lit and has mapped the things very clearly and nicely. I am in middle of learning Machine Learning and has completed 80% of it. But still feels like as if something is missing. This video gave me insights on what should i go back to and revise and practice better. keep on coming back with quality content, much appreciated.
@@SPIDERMAN-oy4nd I started with stats, python 6hrs videos by Krish naik. And also went through the ml-6hrs one. Later i shifted to build more concepts from campusx, done with my 100 days deep learning playlist and jb zarurt hoti toh I go back to 100 days of ml wali playlist... Well I'm learning this all for computer vision.. I mean tumhare goal pe depend krta. Ki tumhe konsi chezz kitni depth tk master krni hai so yaaaaa that's all
Before starting my master's degree, I thought training a model was as simple as having some data, running model.fit, and using model.predict. But machine learning is far more complex. It involves calculus, linear algebra (everything boils down to linear algebra), and understanding algorithms across traditional approaches, NLP, computer vision, and beyond. While TH-cam videos can help with basic concepts, becoming an expert requires diving into state-of-the-art research and thoroughly understanding the underlying mathematics. Skipping the theory leads to gaps, especially when reading papers. If you aim to innovate, develop new models, and truly understand how machines "think," no video can replace a solid theoretical foundation. Mastery demands significant mental effort. Don't be misled by oversimplified tutorials. THEORY IS ESSENTIAL
Perhaps, THE MOST honest content on this matter: Learning ML.
Hi, could you kindly help me out with this? my OKX wallet contains USDT TRX20, and I have the recovery phrase (clean party soccer advance audit clean evil finish tonight involve whip action). How do I transfer it to EXMO?
This is great advice. Coming from someone working in ML and Robotics since 2018. No BS, to the point advice. This is the only ML learning advice video you should watch.
Holy Fuck I'd have to learn jupyter and python.. yuck.. I'll stick to games and buy some use some AI lib
are u working in india? can we connect ? need some guidance
Hi since you did your BE in electrical with a specialization in robotics can you please suggest how learned robotics it will be really helpful as i am also currently doing electrical engineering and want to go into robotics
@@AdilSayyed-u5k Just have the skills, do projects and showcase them in your portfolio, and prep for interview, find jobs online like in Linkedin and Indeed etc.
You will be good. In sha Allah.
Same here but from Mechanical background
That last part about building off tutorials is very real. I find that most of the youtube guides/tutorials are very basic and meant for beginners, but if you take something basic and implement your own ideas it can become a larger and larger project which helps a ton
This video is fantastic, I started learning ML recently and planed to build my first projects in 2025. The whole video was as if my mind was being spoken out loud as this is exactly how I was planing on doing. This reinsures me. I have a solid math background but always hated statistics. This Khan Academy resource will be soooo helphul. Great video, thank you !
haha same for stats, but now i like it :)
Bhai solid math background btaana compulsory tha, ap to phr Jo week hn math mein un ko demoralize kr rhy hn, is field mein Mt aiye ga, mjy itni mushkil ho rhi hai, tumhaara kiye bny ga, khyal krein Bhai
Stats is super cool if you are looking to draw meaningful conclusions from the math that is done, and relate that to a problem and possible implementations. It's pivotal to empirical research. Once you understand that most of it is understanding data through cleaning it up and looking at it multiple ways - as seen in the common algorithms in 17 minutes video - you have most of the conceptualization down in your imagination. That is most of stats right there, outside of understanding the validity of constructs and methods, as well as their relevancy to fitting the data for interpretability purposes.
You will love it soon. It's not extremely difficult, but it is insightful if you constantly keep in mind what it is showing you as you describe the data through the lens of statistics.
Hey man even I'm just starting, have in depth python knowledge and probability and math from university. Looking for a coding buddy. Interested?
@InfiniteCodes_ Very nice video, would you suggest same topics of algorithms, statistics for someone starting with MLOps (not ML)?
My goodness, if anyone wants to really get into ML this video is IT!
Note: Not for people who say they want to do ML, but in reality just like planning what they will do. (Note to self as well 😅)
😂 That's me tbh
What does your note mean?
@@crazyparrot2786 some people just like planning what they want to do but never actually implement the plan. I think they meant to say that this video is not for these people, it's for people who actually want to do ML for real.
the hardest thing about programming and in general these topics is that it is not straight forward and you know what you need to learn. that is the hard part because then it takes a lot of time and gets boring really fast. nice video
This video is all i needed. I've been into Data Science for over a year now and i have done and learned many of the things mentioned on the video, but at some point i felt like i missed something on my way, and this videos had the answers i was looking for. Such a fantastic road map for ML
so what had you missed?
I have been mindlessly doing random ML concepts and projects without a clear goal or pathway. This video was an absolute game changer. Thank you!
When it comes to ML, I often get lost and here it is a game changer. Thank you for your guidance. I have saved a lot of time.
After going thru many tutorials and introductory videos finally found this one which is to the point and no nonsense. It gave great clarity on the overall journey unlike others who mostly confuses. Great stuff man. I'm definitely going to follow this.
Great content and giving the comments of ppl, who apparently are from the field, I definitively will subscribe!
I just finished my DS bootcamp, and right at the beginning I knew it was an illusion, I would be able to master the whole thing in 3-4 months (even if I am ok at statistics and math). BUT, the 4 months gave me a good overview of the whole. Now, I am going back and started again to recap and practice, starting with python and dataviz.
This video is superb. I have 300 years of experience in the field and this is the best video yet.
Wow what talent!
300 years 😭
300 years? Sorry we’re looking for a candidate with more experience.
This is very high quality stuff man. Nice video! - aspiring data scientist
I clicked on this video because im interested in the topic and not necessarily doing ML studies right now, however i am very much a beginner in coding and programming literally started my journey 3 days ago and proud to say i have written my first short code from scratch during my exercises, not sure if this is common in people in this field i just know a lot quite in later after few weeks the videos in this channel and other useful channels help keep me motivated and excited to keep learning i am finally pursuing what i love and hope you blessed reader as well.
This video is incredible, your entire channel is an absolute gold mine and will serve as an amazing resource for learners like myself and the industry as a whole! Thank you so much for your efforts
The guide I have been looking for ages. Thank you for the content
I was going back and forth with so many ideas. But this it. I now know what I want to do. Thank you very much.
From someone that has (maybe) the majority of the math knowledge that you talked about, I can't emphasize on the importance of the python libraries that you talked about Pandas, Numpy and sklearn, we sometimes forget how important they are especially if you come from a theory based background. Also, If you have some knowledge gaps (especially in the hypothesis tests in stats) you'll have a big trouble trying to make good predictions and/or insights.
Also, I want to make a point on the part when you talked about calculus, I think it's important to study not only derivatives of single variable function, but also for multivariable ones, because it's important , for example to understand from where the estimators formulas in multiple linear regression came from.
Good advice.
Best short yet informative story about Data Science Journey ever to be found! 👏🏼👏🏼👏🏼👏🏼👏🏼 thanks!
This video pretty much covers A LARGE amount of a Data Science bootcamp I went through recently, very accurate step by step on how the content was made for us. To add, the VARIETY of jobs you can apply for just from these skills alone. Great video IMHO!
I have been stuck in tutorial hell and this video made me realize it 😅 thanks for the content! will try now and do some projects of my own
Looking for a coding buddy. Interested?
Am up@@lunaT-m5l
Dame I am glad I clicked on this video I was very confused what to do and where to get the resources.from now iam happy that I found this video ❤❤❤❤
Grateful for the video brother, You just saved me hours of banging my head against the wall of youtube creator claiming to build a roadmap for ML and tell BS. Thanks again😭
so far this is the best video I found about ML, simple, focus and fast. Thank you so much!
so much clarity gained from this video. thank you so much!
Great video, I will save it so I can rewatch it any time I need to remember how to become a ML expert.
Very nice video, you basically summed up what I do as a master data science student. Seeing it all presented in a video, I have realized how much I have learnt already.
Thank you. Im sure this will be just another comment and sink down, but still I thanks you for this.
Many people dont know the milestones in learning anything. You provide it really good. Perfect.
This is a great video. Only the How to learn part alone has some great tips not only for ML but learning something in general with efficiency.
I love your videos so much because finally, I have found someone who actually teaches me the real knowledge.
Thank you for sharing the cleanest ML roadmap in such a beautiful video. I really appreciate your guiding and helping others. The video description contains all the useful links, which is a bonus.
Exactly what I've been looking for as I journey down this rabbit hole. Saved and subscribed.
I have some questions:
-Do I need to algorithms and data structure course
-How I can learn maths and steal remember what I learnt before ?
Absolutely the best one I have ever encountered 🙌
Really appreciate your efforts and experience 🙏
Two Thumbs up! A true Masterpiece.
1:01 barista 💀
Bartender made the list too😂😂
Best road map & explanation that I've ever seen, thank u
read first half of 3 great text books on
calculus, linear algebra, statistics and probability
learn python pytorch numpy
thats where i would start
This is possibly the most important video you've ever watched. I wish this existed 10 years ago.
After watching this amazing video, I have checked out multiple other videos on your channel. The content you and your team made is incredibly invaluable to the industry. Keep up the great work and the channel will grow exponentially. Thank you for the knowledge.
This is such a great video! So much really good advice squeezed into a 15 minute video. It almost feels unfair that this is freely available. Now I have to actually implement the advice...
This is what i look for very long time. Thanks a lot
Wow !!! Thanks man . Its awesome 😎
ive been trying to find something similar to this thank you
Great job You have done !! I'm a new subscriber
Yo. The video quality is amazing. I wish you millions of subscribers
You're a absolutely GEM 💎 bro thanks for sharing that Ideas absolutely love it.
I am one of those that has been stuck in 'tutorial hell', I'm going to follow these recommendations to the latter.
Best video ever ❤👌
Just when I need it! great!
Amazing video! Thank you!
The video is insanely amazing!!! Thank you very much, bro !! You made it very simple for me to start !❤
Great video! Best video i have seen so far! Thanks
Please create more tutorials regarding the ML roadmap so that we can learn along with path. Thanks a lot for the info
Great Advice..... Subscribed !!!!
Here’s the corrected version:
I actually get trapped when I see tutorials and copy-paste the code. but now i back to my correct path.❤
Really high quality material, you get my vote
Thanks for the video, it is really helpful!
Thank you sir ❤
The timing of this video has been perfect. Subscribed!
also, don't go into ML (or data science in general) if you're just intrested in results.
If you want to make the next big ai business, go to business and leave the code alone.
If you want to add AI to your projects, learn fine tuning and prompting properly.
If you like math and looking at numbers change, go to data science.
If you're a data scientist (or on the path towards data science) try out making your own model, it's a really fun project
Great info ...gives the much needed confidence!!thankyou ....one request also ...what if some suggestions for interview prep (aptitude/behaviourQ's/situational questions)
Excellent, You said right, You’re the Best Guide.
Loved the vedio ❤...One request,can you make Vedio on how to find research papers to stay updated
i have done most of the stuff thanks for giving me motivation
This is the best motivational video and roadmap i came across. You assured me i am on the right path. ;))) I work in aviation, but as a cabincrew, i dont have much access to databases and if i did it would be illegal anyway XD as a person who is into ML for long time do You have any sugestions about what data i can use and where i can find some aviation enthusiast to colaborate on data analysis projects?
I have been studying ML for the last 2 years and trust me I still need to learn a LOT!
i learned ML, along with time series, recommendation system with help of mythical indian TH-camrs like campusX and krish naik in 5 months ... now I'm also learning MLOPS with azure ... in span of 1 year I learned ML,DL,NLP,cloud,MLops,SQL,pyspark,hive etc ... indian community has best teacher for ML,DL and now I'm an intern at MNC ...
hey man i'm a fellow learner too just a little confused , i would like to connect with you ...are you open to it?
Can you tell me more details if possible?
@@RahulAdhi-dx6hg I think it's just an ad. One can't simply learn all that material in only one year. The material is far too heavy.
One thing I would suggest from my son's experience of learning ML is, no matter from where you are learning. But, always try to focus on the platform which provides hands-on learning. For instance, my son learnt ML from Moonpreneur where he was provided with hands-on learning experience along with theoretical knowledge.
Good One. Loved It.
One of the most practical and sensible vid.
This video is very informative.
Short but very precise.
i am currently learning nlp and transformer have a quite depth understanding of this i think i need to study more research paper to get into this field
This channel is amazing! Thank you so much
Thank you for your great content.
Thank you soo much, It helped me a lot and also it was very relatable to me
Very nice video
It really helped me to understand how to proceed and plan ❤😇👍
This video is a gem
Thank you very much, a lot don't expose that "how to" knowledge honestly. Thank you
Such a high quality video holyy…
Best video for beginners
This video is lit and has mapped the things very clearly and nicely. I am in middle of learning Machine Learning and has completed 80% of it. But still feels like as if something is missing. This video gave me insights on what should i go back to and revise and practice better.
keep on coming back with quality content, much appreciated.
Kya bta sakti ho kaise start ki ML ki journey 😢
@@SPIDERMAN-oy4nd I started with stats, python 6hrs videos by Krish naik. And also went through the ml-6hrs one. Later i shifted to build more concepts from campusx, done with my 100 days deep learning playlist and jb zarurt hoti toh I go back to 100 days of ml wali playlist... Well I'm learning this all for computer vision.. I mean tumhare goal pe depend krta. Ki tumhe konsi chezz kitni depth tk master krni hai so yaaaaa that's all
@@BMEANJALITHAKUR insta I'd ya telegram I'd mil sakta kya
@@BMEANJALITHAKUR insta ya telegram I'd milskti
@BMEANJALITHAKUR we can contact each other any social media
best video on this topic 💯
Before starting my master's degree, I thought training a model was as simple as having some data, running model.fit, and using model.predict. But machine learning is far more complex. It involves calculus, linear algebra (everything boils down to linear algebra), and understanding algorithms across traditional approaches, NLP, computer vision, and beyond.
While TH-cam videos can help with basic concepts, becoming an expert requires diving into state-of-the-art research and thoroughly understanding the underlying mathematics. Skipping the theory leads to gaps, especially when reading papers.
If you aim to innovate, develop new models, and truly understand how machines "think," no video can replace a solid theoretical foundation. Mastery demands significant mental effort. Don't be misled by oversimplified tutorials. THEORY IS ESSENTIAL
What an amazing channel
Really helpful! Subscribed
3:30 should be using a context manager
Really good presentation and advice.
thankyou so much
an actually good tutorial, thanks
Man you are amazing! Thank you very much.
just master piece
This is a great video thanks
dude just saved the whole gen ):
Great content!
Great❤
Good video, very detailed
my god your study approach can also be apply to other stuffs and not just LM dude. Im in Logistics and I find your method pretty efficient ngl.
thank you so so much
Thank you!