Best course you can get for learning ML is this only. Explanation is super awesome. Actually most of the books and courses shows you complex looking mathematical equations but this guy made all that easy for us.
Sir, I know so surely that I can bank on your data science and python videos when I need to gain an in-depth understanding. Your content gives me the hope and clarity that I needed. God bless you and your undying passion to make such useful content for us. Thank you so much for all your hard-work sir!!! :)
For the first time after so many courses, videos, whitepapers, github, kaggle, exercises, wiki pages I am genuinely enjoying Machine Learning and I am doing all the coding and exercises by myself obviously after learning and understanding it all. Thanks a lot!!!
Glad you like them Riya and I wish you all the best! I have many playlists and recently left my job to focus on online teaching. My goal is to produce even a better quality tutorials then this.
@@codebasics One question here. Why we did not remove one of the dummy variable after dropping salary column in Logistic regression like we did for Linear?
On first attempt, i considered 'left' as dependent variable and everything else including salary and department as independent variable, got 77% score of accuracy. Thanks for the wonderful video.
You are the best teacher! I love the exercises at the end of each topic, which strengthens our understanding of what we learnt!!! Thank you so much! :)
I work in a bank as a software engineer. This channel is a gem as this explains the ML concept in laymen terms. I was able to give most of the answers related to ML because of codebasics and deep learning Andrew Ng course
I love your tutorials. They're perfectly paced, with right amount of context and explanation, great examples, and patient but efficient delivery. I hope you continue to produce more. Subscribed here and also Liked all of the videos I've found so far from you. Best.
This video is fantastic. I'm teaching myself machine learning and this was one of the most helpful resources I've found online. Excited to watch/work-through the rest of the videos! Thank you so much
amazing. astounding. bewildering. breathtaking. extraordinary. impressive. marvelous. miraculous. even all these adjectives are less to tell the quality of the video. Thanks a million.
Dear Sir What a beautiful datasheet you have provided for practice with this video. Spent more than two days to play with it. Playing with the datasheet opened another dimension of the learning curve. Thank you very much for providing relevant exercises like this as a challenge!
@@codebasics 15:35 I can’t execute it?? model.predict(57) and any number like 25, 60 got the following ValueError: Expected 2D array, got 1D array instead: array=[57].
@@nxbil2397 that will show you the overal accuracy of your model. My question is , how you will get the probablity % that the employee will leave given the dependent variables? Like the one you have mentioned "satisfaction level".
Hi, i found your course is truly enhancing the path towards Machine Learning concepts, kindly continue this and sir achieve a complete set of this machine learning course including all the kick start algorithms. Thanks Sparsh
Thanks for appreciation Sparsh. I am continuing the series, it is just that due to my schedule I am not finding lot of time to work on it but I will try my best to speed up new tutorial additions.
@@codebasics You are a life saver! Just keep up a great content and if I ever see you, I need to buy you a drink or something for all of this, thank you a lot
thank you so much ! you have helped alot in learning the algorithms. Saved time with such a quick and easy way of explaining as I didn't have time for my fyp compleion and these videos are saving my time to get an idea of all algorihtms
This video had good information, it was really helpful. I am still a learner, new to this field. I understand how to write and basics of confusion matrix using binary classification. But some terminologies are confusing. Can you please explain what exactly are base rate, test incidence, conditional incidence, classification incidence? That would be appreciated.
Hello Sir! Great work by you. there is a problem in your code may be due to version of python .... If we use X_train, X_test, y_train, y_test = train_test_split(df[['age']],df[['bought_insurance']],train_size=0.9) then only we get score of 1 otherwise with your code it is 0.66.
Check out our premium machine learning course with 2 Industry projects: codebasics.io/courses/machine-learning-for-data-science-beginners-to-advanced
I have never seen any other video explaining the concepts of machine learning so clearly. Keep up the great work..!!
Finally i got perfect trainer for ML, your skills are excellence sir, we are very proud of you sir.
Glad you liked it :)
Yes is good but if you like his tutorials then tell your friend to subscribe his channel and hit the like button... that we can do from our side
Best course you can get for learning ML is this only.
Explanation is super awesome.
Actually most of the books and courses shows you complex looking mathematical equations but this guy made all that easy for us.
Perfectly balanced video. It forces anyone to continue to watch other videos of this series. Very well explained in simple language. 👌
Perfect explanation with proper examples. Great job.
medium.com/trainyourbrain/would-you-read-this-article-or-not-b757d0e26cf8
Sir, I know so surely that I can bank on your data science and python videos when I need to gain an in-depth understanding. Your content gives me the hope and clarity that I needed. God bless you and your undying passion to make such useful content for us. Thank you so much for all your hard-work sir!!! :)
i'm Not afraid to learn things with complicated term anymore! this teacher is the best at explanation.
@@codebasics You are good at it. I thank you.
One of the few videos that clearly shows the training data that the model is attempting to fit to. Thank you.
Actually, I fine tuned my model and was able to achieve an accuracy of 1.0. Thankyou so much sir. This might just be the best channel I have seen.🥳
Hi, I have some slight problem. How can I plot the prediction curve after training my model? Would be glad if you reply. Thanks
Could you pls tell me what exactly did you do to fine tune it?
If your testing data is so small then you can achieve accuracy 1 very easily @@anishagarwal71
For the first time after so many courses, videos, whitepapers, github, kaggle, exercises, wiki pages I am genuinely enjoying Machine Learning and I am doing all the coding and exercises by myself obviously after learning and understanding it all. Thanks a lot!!!
Glad you like them Riya and I wish you all the best! I have many playlists and recently left my job to focus on online teaching. My goal is to produce even a better quality tutorials then this.
@@codebasics I am trying to follow all of your videos to improve in my career. I am trying to get a job with a clear concept.
@@codebasics One question here. Why we did not remove one of the dummy variable after dropping salary column in Logistic regression like we did for Linear?
@@riyamitra8901 I think ...as logistic regression can handle multicollinearity between the dummy variables so it's not necessary to drop the last col.
You make people feel so welcomed to data field with your teaching skills. You are always the best.
Why didn't you plot the sigmoid curve but only showed the scatter plot?
On first attempt, i considered 'left' as dependent variable and everything else including salary and department as independent variable, got 77% score of accuracy. Thanks for the wonderful video.
Great job manu. its a good score. Video description has a solution link, you can verify your code with mine.
Started learning machine learning on your youtube.
Absolute Masterclass , you are my real teacher sir!!!
You are the best teacher! I love the exercises at the end of each topic, which strengthens our understanding of what we learnt!!! Thank you so much! :)
I am glad it was helpful. :)
I never seen anyone explaining simple as like this.
Others making complicated like maths intuition.
Thanks code basics
78 percent accuracy. I do all your exercises but in this I learned a lot. Thank you sir for such a great series @codebasics
Hi bro....
Now I learn machine learning....
Now What are you doing. I mean study or work
I work in a bank as a software engineer. This channel is a gem as this explains the ML concept in laymen terms. I was able to give most of the answers related to ML because of codebasics and deep learning Andrew Ng course
bro you are best .. tried to swirl thru other online videos and then I end up watching your videos and I understand better .
Sunnny Singh, I am happy this was helpful to you
Any update you can give how's your data science journey is going as I am aspiring to be a data scientist..
I love your tutorials. They're perfectly paced, with right amount of context and explanation, great examples, and patient but efficient delivery. I hope you continue to produce more. Subscribed here and also Liked all of the videos I've found so far from you. Best.
👍🤗
This is my week 18 of AI Roadmap so far everything is going perfect, and i just wanted to thank you for giving me right direction.
This video is fantastic. I'm teaching myself machine learning and this was one of the most helpful resources I've found online. Excited to watch/work-through the rest of the videos! Thank you so much
medium.com/trainyourbrain/would-you-read-this-article-or-not-b757d0e26cf8
I only could get 77 with logisitic, but then i used lazypredict to find a higher accuracy and then used desicion tree classifier to get a 98, ty!
Thank You Sir, I have learned a lot from your vids :). I was really perplexed by Logistic Regression and I am glad
UA-cam recommended this to me :)
I have no other words to say, the comments done by others have already conveyed my message to you!, Lots of love and thank you !
Thanks a lot for the lucid explanation.
In the exercise, I got an accuracy of 77.2% in my model prediction.
Hi bro...
Now I learn machine learning...
What are you doing.... I mean study or work
Thank you again! Great explanation! Always great tutorials!
Thank you very much for the videos on ML, AI, Python, etc. They help me learn a lot. Your explanations are clear and well understood. Thanks.
George I am glad 😊
amazing.
astounding.
bewildering.
breathtaking.
extraordinary.
impressive.
marvelous.
miraculous.
even all these adjectives are less to tell the quality of the video.
Thanks a million.
ha ha .. nice. you made my day with this shower of praise Siddhant. Thank you for your kind words :)
I paused the video and commented, it's an excellent series that begins with ML.
Thnaks a lot for theese amazing contents. I have just discovered your videos!
Dear Sir
What a beautiful datasheet you have provided for practice with this video.
Spent more than two days to play with it.
Playing with the datasheet opened another dimension of the learning curve.
Thank you very much for providing relevant exercises like this as a challenge!
Happy that this is helping you Nilupul.
Great explanation, I've understood everything, thanks!
Glad you found it helpful!
it is one of the fantastic videos about Logistic Regression .. Many thanks
Many thanks this is the first explanation that provides context and examples making its so simple to understand.
Glad you liked it Michael
@@codebasics 15:35 I can’t execute it??
model.predict(57) and any number like 25, 60 got the following ValueError: Expected 2D array, got 1D array instead:
array=[57].
Daily 2 videos of your ml playlist completes my day❤
Another Great Tutorial, Thank you sir, Waiting for the next tutorial, keep up the good work
one of the best explanation I've ever seen
I love your series of videos as you are concerned with the student's learning! Thanks!
Very interesting and useful - well presented too
Actually you are the best explainer
Thanks a bunch, Subscribed here and also Liked all of the videos I've found so far from you. Best.
Awesome as always, thanks for everything!
i got a 77% model accuracy based on the satisfaction_level
How did you get the prediction model accuracy by depedent variable? And 77% meaning is the probability that they will leave the company?
@@jsbean8415 model.score()
@@nxbil2397 that will show you the overal accuracy of your model. My question is , how you will get the probablity % that the employee will leave given the dependent variables? Like the one you have mentioned "satisfaction level".
Why do we write x and y arguments in split method? Is it because of syntax?
Thanks a lot for this i was able to implement logistic regression after so many tutorials
Your way of teaching is very good. Thanks for the video ❤❤❤
You are the best teacher
Dhavel you are excellent in explaining difficult concepts in very simple language!
I am happy this was helpful to you.
I got 78.833 accuracy value. In this exercise i had known lot of things thank you bro.
I also got around ~78.5% using the average monthly hours and satisfaction level. Did you use the same features??
That’s the way to go Magesh, good job working on that exercise
Thank you very much ! Your videos are always my best choice to learn ML
Thanks one of the best tutorials !
Glad you liked it
God bless you and may He provide angles to solve all your problems. Thank you
Finally got the Python version of Andrew Ag's machine learning course. With a better explanation.
thanks.
😊👍
Perfect explanation!
Glad it was helpful!
This video is really really good. Love the way you teach, your pacing and all the things you mentioned are really useful. Thank u and may god bless u!
Glad it was helpful!
Sir I tried this method, it is very easy to understand and use.. thank you sir
Sir, I extremely appreciate your videos and efforts in teaching these things. Very helpful and great explanation!!
Nice Sir, try to create SVM or PCA next with some mathematical explanation. thank you
Your videos are awesome. I'm learning so much!
Hi, i found your course is truly enhancing the path towards Machine Learning concepts, kindly continue this and sir achieve a complete set of this machine learning course including all the kick start algorithms.
Thanks
Sparsh
Thanks for appreciation Sparsh. I am continuing the series, it is just that due to my schedule I am not finding lot of time to work on it but I will try my best to speed up new tutorial additions.
Thanks, sir .. your explanation is really clear and so easy to understand 👍🏼
thank you sir for your video.
very useful video.... you explain everything in a very simple manner. Thank you
Glad it was helpful!
Sir Kindly confirm whether you already have a video for how to do Exploratory data analysis and feature selection. Thank you.
sir please start Deep learning tutorials :)
I am going to start that in next few days. Stay tuned :)
@@codebasics You are a life saver! Just keep up a great content and if I ever see you, I need to buy you a drink or something for all of this, thank you a lot
Awesome explanation. I like this practical math and algorithmic explanation.
Exactly what I was looking for, Thank You!
0.84 accuracy score and 0.83 mean cross validation score.
Thanks, Your tutorials have been helpful.
how?
Very Clear Explanation
Glad it was helpful!
Great Class, you are the best of the best !!!
clearly understandable explanation.
Thank you so much.
thankyou for making videos, your content is great
just subscribed, your very good at explaining. thank you!
I am glad you liked it Pablo
Thank you so much for the graphical explanation...the concepts are crystal clear in my mind now.
nice explanation ever sir .
among several videos, this one is the best. appreciated
Rida, I am glad 😊
Very good explanation
Thanks. It is really informative.
Thank you so much, sir. I've got the score in the exercise 0.797. 🙂
Very nice and you present easiest way to understand. Thank you
Thank you sir for this amazing explanation of Logistic Regression.
Glad you liked it
Very well done and explained even for beginners - thank you so much!
You guys are life savers. man love your videos.
Amanullah, I am happy it helped you :)
Perfect explanation on logistic regression.
Loved it. Thanks a lot.
medium.com/trainyourbrain/would-you-read-this-article-or-not-b757d0e26cf8
Sir, why didn't you drop one of the salary column after categorizing it using dummy variable in the solution ?
Yes, why didn't you drop one column after one-hot encoding? If you didn't drop it, then you will encounter a dummy variable trap, isn't it?
Yea, same question. I think we should drop one of the low,med,high salary columns
@@Fengin221 Why to make data complex, there are only 2 columns in the dataset. And there aren't any Nan values.
@@vishaldas6346 we should drop a column to avoid multicoliniarity.
e.g the Low and med cols can predict what is on high column.
It is actually not necessary it is intelligent enough to not to fall into the dummy variable trap.
Hey plz tell me what to do when I have multiple Columns like age ,weight , bmi that i need to consider for prediction
thank you so much ! you have helped alot in learning the algorithms. Saved time with such a quick and easy way of explaining as I didn't have time for my fyp compleion and these videos are saving my time to get an idea of all algorihtms
I like your tutorials very much, the explanation therein is superb and makes one understand even very hard to grasp concepts.
This video had good information, it was really helpful. I am still a learner, new to this field. I understand how to write and basics of confusion matrix using binary classification. But some terminologies are confusing. Can you please explain what exactly are base rate, test incidence, conditional incidence, classification incidence? That would be appreciated.
Bro it was easy and clean. Thanks!
lol i just love the part on the exercise when he sayed you are a data scientist.
The best explanation as always
Glad you liked it
Very well explained, thanks!
Glad you enjoyed it.
Well explained, Thanks!
Amazing lectures.
Glad you like them!
awesome explanation....really
😊👍
If you could build a machine learning model for HR department, then you can remove HR department 😂😂
Thank u so much..it really helped to clear my concepts
Hello Sir! Great work by you.
there is a problem in your code may be due to version of python ....
If we use X_train, X_test, y_train, y_test = train_test_split(df[['age']],df[['bought_insurance']],train_size=0.9)
then only we get score of 1
otherwise with your code it is 0.66.
OMG. I was trying to run the code and did not know why mine was 66%. Thank you for this !!!
Thank you! So well done