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@NASAverseExploration2 күн бұрын
You're really good at explaining everything. This is really a beginner friendly project where we can learn and understand. Thankyou so much Alejandro❤
@alejandro_aoКүн бұрын
I appreciate it!
@primefindz4 күн бұрын
thanks , the way you tackle each part of the project helps beginners like me learn and catch up easily
@alejandro_ao3 күн бұрын
it's my pleasure! :)
@ahmeddiaa518216 күн бұрын
Hello, great video just one comment is at 22:04 the reason it's recommended to convert it into a categorical type is that python/the model will treat it inherently as an int type which indicates that one is larger or greater than the other 1 > 0 which is not what we're looking for we want the model to treat it as if 1 is a yes and 0 is a no basically otherwise great content and i hope this helps
@ayoajayi2807 ай бұрын
This video is highly educative. I wish he explains other ML algorithms in future videos. Thanks so much.
@lasithdissanayake26 күн бұрын
Great explainations, clear instructions and great work. I wish you could do more projects on other ML models as well. That would be really helpful. Thanks for this content man.
@alejandro_ao26 күн бұрын
it's my pleasure, mate. i am have been focusing much more on genai recently, but i'll try to make more regular ml content too!
@lasithdissanayake26 күн бұрын
@@alejandro_ao thanks. I clarified a lot with your 2 videos of linear regression and logiatic regreasion. Thats why. Anyway, talking about genAI. Can you help with building a chatPDF app using a free LLM like groq
@alejandro_ao26 күн бұрын
@@lasithdissanayake that's great to hear! absolutely, that is coming up very, very soon actually. i just need to finish putting together a course in genai that i will release in the next few weeks. but i should be able to put out that video within a couple of weeks 😎
@lasithdissanayake25 күн бұрын
@@alejandro_ao great buddy. Thanks for the amazing content. Love from Sri Lanka ❤
@dazai6861 Жыл бұрын
A standard scaler 30:00 transformers your values into a range of (-3 ; +3) Thank u for the video.
@for-ever-22 Жыл бұрын
This is one of the best videos on data science and I have seen a lot . Thank you for this. Please keep posting
@emekaejike15Ай бұрын
I think its because the X variables are what we need for our predictions. The Y variable is just a result of the X variables
@sasuke95014 Жыл бұрын
Great video. Thank you.
@edmashokmusic1692Ай бұрын
this is the best tutorial i have ever watched. thanks a lot man. And Instead of train, test. is there any benefit of using train, validation, test?
@majydenam94233 ай бұрын
Great work ...Thanks
@mellowbeatz937 ай бұрын
unbelievable I learned a lot from you!!! Thank you so much! Cant wait to check your new tutorials, truly the best channel for beginners who wants to deep dive into AI! Is it possible that you can make a tutorial how to build an API around it or even how how to deploy it with e.g. Flask? (as you stated it in your conclusion) ❤
@RaihanRisad3 ай бұрын
informative and useful, you should make it a video on how to deploy it using flask or any other thing
@arthurcwlau930710 ай бұрын
Great teaching! I am new to Python and ML and am learning a lot! How to handle if the predictor is categorical in nature, e.g. some Yes/No or 0/1 of something, but not a number/measurement. Can the logistic regression model handle that?
@tejaspatel221210 ай бұрын
Best video i have seen.. such an amazing explaination. can you please come up with more ml projects instead of langchain?
@prisharai7928 күн бұрын
thank you brother
@alejandro_ao8 күн бұрын
you're welcome brother
@admonitoring-pi9osАй бұрын
thanks
@alejandro_aoАй бұрын
it's my honour
@shivammehra321714 күн бұрын
Isn't you had to first split the data then normalized? the way you did would cause data leakage.
@ayoajayi2807 ай бұрын
Great video. But I have a question. While wasn't the y variable normalized. Only the x variables were normalized?
@espinozagarciafelipekaleb9881Ай бұрын
The Y variable is our target variable, so we have to be careful in not changing it's values because if we change them we can change the entire purpose of the model. Also, we normalize the independent variables to avoid "confusing" our model with a magnitude bias, the bigger the magnitude of the variable compared to the other, the bigger the bias in the training of the model so that's why we normalize, but for the target variable there is no need to normalize because the model Will predict the value, in this case 0 or 1, if we normalize the model would predict something different and to the length of my knowledge I don't think that we can interpret that correctly just yet (Sorry for the bad English) greetings from mexico ✌🏻
@primefindz4 күн бұрын
why 42 for random state?
@alejandro_ao3 күн бұрын
because it's the answer to the ultimate question of life, the universe, and everything , of course