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Hey AJ, why didn't you make vdos on other algorithm man, this is the first thing i understood well , so neatly explained , you my saviour ,plz make more algos !
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
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_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
@@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 😎
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?
Just wanted to say amazing video. Also at 9:07 when you talk about the equations, shouldn't the logistic regression equation be 1/(1+e^y) instead of e/(1+e^y) Just noticed that but thanks for your videos, they are amazing ways to implement what im learning in projects!
best about your video is u do some eda also m0st of the yter those is explain the model and implementing them straight but u do some serious work keep up i am watching u brother
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) ❤
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 ✌🏻
so after we have trained the model, how can we input fresh values for all columns but diagnosis and see the output guessed by the model (ie we do not have the diagnosis yet, we want it from the model first). So how would we go about it?
💬 Join the Discord Help Server: link.alejandro-ao.com/981ypA
❤ Buy me a coffee (thanks): link.alejandro-ao.com/YR8Fkw
✉ Join the mail list: link.alejandro-ao.com/o6TJUl
Hey AJ, why didn't you make vdos on other algorithm man, this is the first thing i understood well , so neatly explained , you my saviour ,plz make more algos !
Thanks for teaching and guiding in so descent way
This video is highly educative. I wish he explains other ML algorithms in future videos. Thanks so much.
I know this video is about a year old, but this was an amazing walk-through. I really appreciate it!
Simple and hence easy to understand, would love to learn from your videos the other topics too. Thank you.
Amazing teaching man.....
Very much articulated...♥
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
Man You Did Awesome.. I can't buy coffee for you for now...but hope so in Future.. please continue building models
thanks! i will :)
@@alejandro_ao my class is over just now and we learned decision tree ... Please upload all models videos
A standard scaler 30:00 transformers your values into a range of (-3 ; +3)
Thank u for the video.
thanks , the way you tackle each part of the project helps beginners like me learn and catch up easily
it's my pleasure! :)
Thank you bro for teaching.
This is one of the best videos on data science and I have seen a lot . Thank you for this. Please keep posting
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
You're really good at explaining everything. This is really a beginner friendly project where we can learn and understand. Thankyou so much Alejandro❤
I appreciate it!
Great explanation and real case example, thanks a lot
it's my pleasure!
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.
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!
@@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
@@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 😎
@@alejandro_ao great buddy. Thanks for the amazing content. Love from Sri Lanka ❤
Your content is amazing! Thanks!
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?
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?
Just wanted to say amazing video. Also at 9:07 when you talk about the equations, shouldn't the logistic regression equation be
1/(1+e^y) instead of e/(1+e^y)
Just noticed that but thanks for your videos, they are amazing ways to implement what im learning in projects!
best about your video is u do some eda also m0st of the yter those is explain the model and implementing them straight but u do some serious work keep up i am watching u brother
i appreciate it sam! glad to hear this was useful!
Great video. Thank you.
informative and useful, you should make it a video on how to deploy it using flask or any other thing
Best video i have seen.. such an amazing explaination. can you please come up with more ml projects instead of langchain?
keep it up bro
thank you brother
you're welcome brother
Great work ...Thanks
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)
❤
Isn't you had to first split the data then normalized? the way you did would cause data leakage.
Great video. But I have a question. While wasn't the y variable normalized. Only the x variables were normalized?
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 ✌🏻
so after we have trained the model, how can we input fresh values for all columns but diagnosis and see the output guessed by the model (ie we do not have the diagnosis yet, we want it from the model first). So how would we go about it?
Amazing
you are
@alejandro_ao please make more ml projects
Isn't that linear regression at 5 minutes heteroscedastic?
thanks
it's my honour
why 42 for random state?
because it's the answer to the ultimate question of life, the universe, and everything , of course
hey brother, i have a small request and i hope that my request will be heard. please make more videos on different algorithms
thank you
hey brother. actually i was not considering this, but now i see more and more people interested in this. so i will be making some more, for sure :)