I solved the exercise and my model got an accuracy of 96.67% Thanks for making such great videos.
@sonalgarg56284 жыл бұрын
@@anujvyas9493 can you please send the solution..i also got same accuracy but unable to do prediction
@anujvyas94934 жыл бұрын
@@sonalgarg5628 Sure! Email ID ?
@sonalgarg56284 жыл бұрын
@@anujvyas9493 sonal.garg@gla.ac.in
@anujvyas94934 жыл бұрын
@@sonalgarg5628 Sent it to you! Sorry for the late reply.
@peiyuankao12135 жыл бұрын
Thanks for your teaching! I like your tutorials and exercises, that make me quickly understand.
@maruthiprasad81842 жыл бұрын
I got accuracy 93% for iris data set. Thank you very much to make ML simple.
@rayithki2 жыл бұрын
Thank you. I wish I had discovered your channel 6 months ago. I could have saved so much time.
@PoojaPatel-bi4wr Жыл бұрын
Sir , Whatever you teach it's very very interesting and I think I am luckiest person which I am reading from your videos It's very helpful for us and you are great. I have seen many videos but no one teaches like you.
@Ankurkumar146805 жыл бұрын
Great tutorial, thanks a ton for shaing this amazing stuff. Request you to start a series on NLP, Deep Learning or Text Analytics
@SohamPaul-xy9jw Жыл бұрын
Thank You. After watching previous 8 videos, I tried this Iris exercise on my own and my model actually predicted so well, with a score of 1.0
@satyazigyansu68739 ай бұрын
it is overfitting bro
@parththakor73625 ай бұрын
@@satyazigyansu6873 accuracy is varies with random state and test size random state = 42 and test size = 0.2 then accuracy = 100% random state = None and test size = 0.3 then accuracy is around 97% and it varies every time
@yashchaudhari52893 ай бұрын
@@satyazigyansu6873 no brother it depends on dataset whether it is testing or training. If it is on testing dataset then it is not overfitting, if it is is on training dataset then it is overfitting.
@wsgsantos5 жыл бұрын
As always great video. Greetings from Brazil!
@jagjeetagarwal18562 жыл бұрын
Within 2 Days I have addicted to this channel......I am on this Channel for around 5-6 hours Continuously....... Please Continue the Series......Thanks
@jayshreedonga2833 Жыл бұрын
Thanks sir. Simply you are great for such type of free courses.Nice service to society
@stanlukash333 жыл бұрын
I CAN'T SAY THIS ENOUGH - THANK YOU!
@pallawkumar98465 жыл бұрын
Thank you for these awesome tutorials. Please upload next tutorials.
@-theworldofscience41532 жыл бұрын
The contents are actually very engaging and helps u tolearn complex topics very easily
@masterofnone7543 жыл бұрын
probably the best tutorial series for beginner thank you!!!!!
@codebasics3 жыл бұрын
Glad it was helpful!
@nitinsrivastava21365 жыл бұрын
Awesome. Thanks for sharing. I love the way you teach topics. So easy to understand. Thanks again.
@codebasics5 жыл бұрын
Yup nitin, things don't have to be taught in a hard way.. there is always an easy way to explain the concepts :)
@tcsanimesh5 жыл бұрын
Your explanation is at a different level. Just one request please add the different machine learning algorithms a bit fast as once someone starts leading from your channel gets hooked up to it ...
@nishkarshaggarwal26923 жыл бұрын
you are a great teacher.... thank u for this series
@liangyumin94055 жыл бұрын
Nice tutorial, I have forked your project PY .THX
@rehanabbas4661 Жыл бұрын
Respect and appreciation from 🇵🇰 . Interesting teaching skill. 👍
@jyotimalik89602 жыл бұрын
finalllllly I understood how to interpret confusion matrix for multiclass classification thankyou!!!!
@yoniziv3 жыл бұрын
Very clear, thank you!
@muskan_salampuria4 жыл бұрын
One of the best tutorial... Thankyou so much...It is very helpful and informative.... I wish to see more videos on other topics...
@codebasics4 жыл бұрын
Glad, you liked it.
@Kikeina5 жыл бұрын
A little detail... after updating sklearn to version 0.20.2 or higher it will be needed to specify a solver and multi_class specification as parameters to avoid warning errors. For instance "model = LogisticRegression(solver = "newton-cg", multi_class="auto")"
@russnagel13 жыл бұрын
Thank you very much. You just saved me a big headache. I had the warning and came looking to the comments for help. Great job.
@Kikeina3 жыл бұрын
@@russnagel1 Happy to see that the comment is helping somebody. You made my day.
@dhruvpathak1850 Жыл бұрын
Very helpful, I tried using max_iter / n_iter to 200, in the model.fit() part, but that didn't work either.. eventually, it's your suggestion that did work!
@drpebba2679 Жыл бұрын
my savior
@dixxanta10 ай бұрын
u can also use standard scaler
@mabelkarani3 жыл бұрын
at 7:50 , use this >> model = LogisticRegression(solver='lbfgs',class_weight='balanced', max_iter=10000) to avoid this warning >>> 'ConvergenceWarning: lbfgs failed to converge (status=1): STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.'
@harsh20143 жыл бұрын
Thank You Mabel Karani , you helped me !
@tanvirahmed5522 жыл бұрын
thanks 😊
@muhammadtayyab2148 Жыл бұрын
thks
@aaditstudent Жыл бұрын
@@muhammadtayyab2148 what was ur accuracy score using the above parameters?
@palurikrishnaveni8344 Жыл бұрын
Thank you madam
@kashifahmad933 жыл бұрын
Got 96.66% accuracy.....while practicing on your given iris.csv dataset...I am new on your channel, but got addicted to your videos, especially to the playlist of machine learning... please keep teaching us in same way. Thanks a lot..
@codebasics3 жыл бұрын
That’s the way to go Kashif, good job working on that exercise
@RahulRaj-cy1xb2 жыл бұрын
Bro we need to download exercise from kaggle? As sir only uploaded image on github
@parththakor73625 ай бұрын
@@codebasics accuracy is varies with random state and test size random state = 42 and test size = 0.2 then accuracy = 100% random state = None and test size = 0.3 then accuracy is around 97% and it varies every time
@jawadasif81302 жыл бұрын
really appreciate your hard work. from your videos it was super easy to learn the concept . thank you
@codebasics2 жыл бұрын
You are most welcome
@pakpoomtivarkornkit85255 жыл бұрын
Thank you so much....liked and subscribed.
@yourlifeonpower4 ай бұрын
Another awesome video! Thank you
@vinodkinoni48635 жыл бұрын
thanks for good tutorials
@rakeshg29265 жыл бұрын
Thanks your tutorials are very clear and intutive and easy to understand.
@codebasics5 жыл бұрын
Rakesh, thanks for your kind words of appreciation
@raghuvamsiyaram7248 Жыл бұрын
I got 96.66 accuracy. Thanks.
@rishipatel22213 жыл бұрын
Thank you so much for this invaluable series
@codebasics3 жыл бұрын
Glad you enjoy it!
@strongsyedaa73782 жыл бұрын
@@codebasics Kindly make a video on confusion matrix multiclass classification please 🙏
@MdAbdurRahaman-f2d7 күн бұрын
one thing i don't understand. in the heat map, you said, if the number was not zero, the model accuracy failed there. but in the first example, 37 times I fed my model zero, and my model said it was zero. same as like, 40 times i fed one and my model said it to be one. So, the accuracy is perfect with not being zero in the diagonal part of heatmap. thanks a lot for your marvelous effort
@rajatpati88085 жыл бұрын
Waiting for your next videos. Hope you will upload soon.
@rambaldotra22213 жыл бұрын
Iris dataset -> 97.777777777777 accuracy with test_size =0.3 I have fallen in love with this amazing knowledge 🤩.Thanks a lot Sir ❤️.
@oilidzaghloul32663 жыл бұрын
I got an accuracy of 1 with test_size=0.2.
@RahulRaj-cy1xb2 жыл бұрын
Bro we need to download exercise from kaggle? As sir only uploaded image on github
@nandithass732619 күн бұрын
pls provide the code
@dennisasamoah22134 жыл бұрын
simply amazing
@mohammedashfaqueaslam25664 жыл бұрын
Amazing content you make it all seem easy
@codebasics4 жыл бұрын
Glad you liked it Mohammed.
@vdud0074 жыл бұрын
Thank you and practice exercises are useful as well
@codebasics4 жыл бұрын
Glad you liked the exercises Vishnu
@nastaran10107 ай бұрын
Thanks a lot, very clear
@golammuktadir43554 жыл бұрын
Good approach for coding the basic machine learning . Carry on
@codebasics4 жыл бұрын
👍😊🙏
@achelias84773 жыл бұрын
On my way to watch your whole playlist. You are a great techer! I got accuracy 95.6%
@codebasics3 жыл бұрын
👍😊 wish you all the best
@olutokijohn2 жыл бұрын
Can you share your solution ?
@aaditstudent Жыл бұрын
What parameters did you use for the LogisticRegression model?
@safwansalehjee79615 жыл бұрын
Is there no Exercise solution?
@hamzanaeem48383 жыл бұрын
Excellent explanation
@nicojapasmusic3 жыл бұрын
Very helpful, thanks!
@codebasics3 жыл бұрын
Glad it was helpful!
@javi198410004 жыл бұрын
Great job, Thank you ver much
@codebasics4 жыл бұрын
Glad you liked it!
@radhedhabas7 ай бұрын
I got accuracy of 96.66%. Thank you so much for your initiative. Best part of your playlist is exercises that give confidence and a clarity how to apply logics in form of code. And best part you talk about practical use cases.
@parththakor73625 ай бұрын
accuracy is varies with random state and test size random state = 42 and test size = 0.2 then accuracy = 100% random state = None and test size = 0.3 then accuracy is around 97% and it varies every time for best way choose random state = 42 or 10
@nandithass732619 күн бұрын
pls provide the code
@radhedhabas19 күн бұрын
@@nandithass7326 please look exercise section in given notebook: colab.research.google.com/drive/1ayUBBqEvH-mDkYHVqMFO6-nlWRyZhyNt?usp=sharing, as I'm using sklearn, accuracy varies every time.
@abhishekkhare61753 жыл бұрын
got accuracy of 93.34%. Thanku very much really addicted to your videos.
@codebasics3 жыл бұрын
Well done
@tanoychowdhury63755 жыл бұрын
Sir, Please make videos on other topics of machine learning like k nearest neighbour , support vector machines. Your videos are very very helpful. please continue this series.🙏🙏
@orangewares5 жыл бұрын
You can refer to videos of sentdex. The videos are much better including k nearest neighbor. kzbin.info/www/bejne/hXjbmKF-bd5lhK8
@nareshjanjirala4725 жыл бұрын
nice tutorila.... by watching your tutorials lot of people are opeining institutes in Hyderabad
@codebasics5 жыл бұрын
Ha ha.. are you serious? 😊
@tewatiakuldeep865 жыл бұрын
Sir your way of describing things is very easy to grab and understand. Thank you for the tutorial. I request you to please also make a few videos of analyzing data (statistics) before using it into a model. Like variable correlation, and what variable should be used and which one should be dropped, etc.
@codebasics5 жыл бұрын
point noted kuldeep and thanks for your appreciation. I want to add lot more content but unfortunately facing health troubles. once i recover I will be back with full force :)
@nayyershahzad80513 жыл бұрын
I got 96.66% accuracy for Iris dataset exercise. Great work! Thoroughly enjoying and learning a lot from your courses.
@digvijaymahamuni77223 жыл бұрын
i got 94.73% does it vary? or have I done any mistakes?
@fazalahmad15463 жыл бұрын
I got 100.0%
@fazalahmad15463 жыл бұрын
@@digvijaymahamuni7722 this is due to a very small dataset
@mohammedsohilshaikh68313 жыл бұрын
@@fazalahmad1546 check for overfitting
@mdlwlmdd2dwd303 жыл бұрын
Hey guys chill it isnt like you guys working in backend developing library. also it is relatively clean dataset already.
@franky02264 жыл бұрын
Thank you so much sir :) I loved the tutorial! , got an accuracy of 97.72 %
@codebasics4 жыл бұрын
Great job!
@nitishkeshri23783 жыл бұрын
how?.....I'm getting only 56%
@bandhammanikanta16644 жыл бұрын
Loving your Lectures sir. Could you please use any best deep learning model for this dataset. Or Suggest me one. :)
@ehsanakbari3519 Жыл бұрын
that was awesome🤩🤩
@vishnuvardhan-wq5qi5 жыл бұрын
my model is 100 percent accurate for iris dataset. thanks for teaching all the topics which are really important in a clean and clear way.
@harshthummar63602 жыл бұрын
I loved this tutorial..! Absolutely awesome...!! i get up to efficiency= 96.6%
@codebasics2 жыл бұрын
That’s the way to go Harsh, good job working on that exercise
@asedaaddai-deseh81525 жыл бұрын
Thanks so much for these great tutorials! I wish you would upload the continuation of this playlist faster so we can learn fast.
@asedaaddai-deseh81525 жыл бұрын
@@codebasics Wow, I admire the fact that you're able to make these videos despite your busy schedule. Keep it up!
getting a score of 1.0, by using newton-cg solver. Default LogisticRegression() shows warning. You can use model = LogisticRegression(solver = 'newton-cg', multi_class='auto') for better training and accuracy.
@coxixx4 жыл бұрын
awesome!
@AnanyaRay-ct8nx Жыл бұрын
got 93.33% accuracy. Thank u so much for this playlist..
@ayushshankarpurkar1417 Жыл бұрын
i also got 93.33% accuracy can you please tell me how you did it I want to cross check my procedure.
@ss57hd5 жыл бұрын
Wow, Your videos are amazing! And i got an accuracy of 96%
@codebasics5 жыл бұрын
great. thanks for working on exercise and congrats on getting such a high accuracy score. Good job :)
@vinays.m68314 жыл бұрын
Sir can u send me that code please... I am not getting that so...
@sujithramanathan32754 жыл бұрын
@@vinays.m6831 PFB code. Please let me know if anything is incorrect. import pandas as pd import matplotlib.pyplot as plt from sklearn.datasets import load_iris from sklearn.model_selection import train_test_split from sklearn.linear_model import LogisticRegression iris = load_iris() x_train, x_test, y_train, y_test = train_test_split(iris.data, iris.target, test_size=0.2) irisModel = LogisticRegression() irisModel.fit(x_train, y_train) targetIndex = irisModel.predict(x_test) for i in range(len(targetIndex)): print(iris.target_names[targetIndex[i]]) irisModel.score(x_test,y_test)
@mansoorahmed41503 жыл бұрын
nice explanation. I have one question. What about if we have mix of dependent variables data, like binary as well multiclass v variables, is it fine we apply multiclass regression?
@pamp3657 Жыл бұрын
Good video.
@wasit-shafi3 жыл бұрын
At 15:33 I thought you are going to say 'plz plz subscribe the channel, like, comment, share... :) Thank you sir for making such a great videos...
@rajareivan2417 Жыл бұрын
so it can only take inputs and predict images from the dataset?, how if i want to predict other images that are not from the digit dataset?
@josiahvanness40373 жыл бұрын
Sir, you forgot to upload the iris flower Solution for ML exercise 8 in you github, there is only exercise description at the end of github file, no exercise folder, no solution. Your tutorial is awesome, everybody is following you to practice. Thank you for teaching us and can you please upload the solution, appreciated.
@RohitSingh-hc8yi6 ай бұрын
awesome
@yoshidasan47802 жыл бұрын
Thank you so much sir !I am so so grateful to you for these wonderful tutorials ,hope i can learn even more and faster.Btw i got my accuracy as 97.77 !
@pranav9339 Жыл бұрын
Bro I got the same but is it correct? How can accuracy be so high? Please can you explain
@yoshidasan4780 Жыл бұрын
@@pranav9339 because the trends are very similar in the test set data too ig and the variance is also low ...that's the reason i think
@mojojojo18545 жыл бұрын
please do tutorials on Computer vision using Tensorflow
@cindinishimoto95284 жыл бұрын
That would be awsome!! ♥️
@shivadumnawar77414 жыл бұрын
I got 100% accuracy for the iris exercise. Sir give more exercise. These are very helpful, thanks a lot sir
@sejalmittal13264 жыл бұрын
didn't you get total no. of iterations reached ??
@sejalmittal13264 жыл бұрын
Can you help me out ??
@shreyjoshi184 жыл бұрын
increase the size of your test data and then check
@sejalmittal13264 жыл бұрын
@@shreyjoshi18 okay .. thanks
@foreveryour11 Жыл бұрын
At 12.17 what we predicted was for X_test. Why did we compare the Y_test and X_predictions? Am i understanding it wrong? 😀
@mlTS76269 ай бұрын
Superb content, liked this very much 12:50, maybe there's a simple mistake that xlabel should be Truth while ylabel should be Predicted, as we have defined cm in that way
@arjunpukale33105 жыл бұрын
How to recognize whether the classification dataset is linear or non linear if there are multiple variables and cannot be plotted?
@syed17424 жыл бұрын
How to visualize decision boundry through plot and how to optimize using log loss function, and whatever you are teaching that teaching everyone.
@sanooosai6 ай бұрын
thank you
@vijaydas29625 жыл бұрын
In both Binary and Multiclass classification example, you have used the SAME algorithm i.e. from sklearn.linear_model import LogisticRegression model = LogisticRegression() Questions- 1. Does it mean, from LogisticRegression perspective, it makes no difference whether it is binary or multiclass classification? 2. Is there any model parameter that we can tweak to define the class boundary. Say, predict the output as - a) "Excellent", if probability> 0.8 b) "Very Good", if probability >0.6 and 0.4 and 0.2 and
@g00dvibes474 жыл бұрын
It’s very late and I’m very tired, but in a nutshell, sometimes you can use regression as a classifier and sometimes binary classifiers are suitable for multiclass classifications!
@tanmaythaker29052 жыл бұрын
Sir done with the assignment. Got 100% train accuracy for iris dataset and also plotted the confusion matrix.
@perikalasunny5698Ай бұрын
sir in this video i think you took x and y axis reverse in labelling the cause in confusion matrix arguments its x and y respectively right?
@cindinishimoto95284 жыл бұрын
Awesome exercise! I got an accuracy of 97, 77%
@aditinagar66884 жыл бұрын
Can you please provide the solution link as it is not there on github? It would be helpful.
@cindinishimoto95284 жыл бұрын
Hi, @@aditinagar6688. Please see below: iris = load_iris() print(dir(iris)) df = pd.DataFrame(iris.data, columns=iris.feature_names) print(df.head()) df["target"] = iris.target print(df.head()) df["target"].replace({0: "setosa", 1: "versicolor", 2: "virginica"}, inplace=True) print(df.head(-10)) x = df.drop(["target"], axis=1) y = df["target"] from sklearn.model_selection import train_test_split x_train, x_test, y_train, y_test = train_test_split(x, y, test_size=0.3) print(len(x_train)) print(len(x_test)) from sklearn.linear_model import LogisticRegression model = LogisticRegression() model.fit(x_train, y_train) print(model.score(x_test, y_test)) print(model.predict(x_test)) #print(y_test) print(model.predict([[4.9, 3.0, 1.4, 0.2]])) #setosa y_predicted = model.predict(x_test) from sklearn.metrics import confusion_matrix cm = confusion_matrix(y_test, y_predicted) print(cm) import seaborn as sn plt.figure(figsize=(10, 7)) sn.heatmap(cm, annot=True) plt.xlabel("Predicted") plt.ylabel("Truth") plt.show()
@tejobhiru10923 жыл бұрын
@@cindinishimoto9528 thank you so much..! this helps a lot.. i was not able to figure out how to handle that dataset!
@cindinishimoto95283 жыл бұрын
@@tejobhiru1092 ^_^
@haiderkhwaja251410 ай бұрын
@@cindinishimoto9528 i also need this exercise code very badly
@hameedali29634 жыл бұрын
great
@nilupulperera4 жыл бұрын
Dear Sir Very interesting exercise. Model accuracy varies from 0.8 to 1.0, each and every time after a fresh run of the full code (as you explained). The average accuracy is around 9.66667. Thank you very much
@pranavkushare51094 жыл бұрын
use (shuffle=False) in train_test_split()
@parasf094 жыл бұрын
accuracy=93.3% thankyou sir
@87prak Жыл бұрын
You should have talked about what scikit logistic regression is doing under the hood for multiclass. The tutorial does not touch on that and simply runs the program as if it were binary class problem. Is it using n binary classifiers or a softmax, that is what should have been discussed here.
@muhammedrajab23013 жыл бұрын
sir I have done the Iris flower exercise according to what I have learnt from you. I got an accuracy of 1.0 (I thing it is 100%) ! I just done everything according to what I have learnt from you!
@codebasics3 жыл бұрын
Perfect and keep it up. The dataset is small hence getting accuracy of 1 is not unusual
@vedanthbaliga76863 жыл бұрын
if you have given random_state or shuffle=True then the accuracy will be 1
@oilidzaghloul32663 жыл бұрын
@@vedanthbaliga7686 even without a random_state or shuffle it s still possible to get 1, it s all due to the fact that our dataset here is small
@leooel46505 жыл бұрын
Can't express how grateful i am to you Sir. I am very willing to even pay for your stuff and help you somehow. Thanks once again, my accuracy was about 92%
@zerostudy75085 жыл бұрын
how much ratio test/train u use? i got 91...%
@leooel46505 жыл бұрын
@@zerostudy7508 20% of the data to be tested. But the accuracy depends as we are getting random data to be trained or tested. My opinion is that your model is correct, we just have different trained data.
@zerostudy75085 жыл бұрын
@@leooel4650 Thank you so much buddy, i just checked that if i use 90% data for train and 10% data test i get 88-90% acuracy, but when i use 80% the data for training i got everage more than 90-100% accuracy. i'll tell you when i figured something out....
@leooel46505 жыл бұрын
@@zerostudy7508 happy to help as I am still figuring things out.
@zerostudy75085 жыл бұрын
@@leooel4650 i got it it something to do with sample and population' if test A=20 and test A=10 then they both got just 1 wrong answer A and B Standard Deviation Sample are A=0.217944947 B=0.316227766 about 10% difference in a nutshell its sound like this: your teacher give 10 questions for exam and your friend got 100, if both of you had 1 wrong answered in the exam, which of you have the highest test score ? have a nice day
@swL19414 жыл бұрын
100% accuracy. Thank You Sir.
@cbbakshi20205 жыл бұрын
Amazing tutorial:) How to make roc_curve for this multiclass problem?
@AlonAvramson3 жыл бұрын
Thank you for explaining this in such a nice and easy way. BTW, I downloaded the whole GIT files but could not find the exercise solution for this session, so If some one has a clue please let me know.
@aravinthm83283 жыл бұрын
Yaa the answer for this exercise is not in the file. I solved the exercise, you can also try in the same way as in the model problem. but in the Handwritten digit problem, i got an error when fitting the model :( , i cant correct the error. It showing 'str' object has no attribute 'decode'. Can you help me to come out from this.
@RahulRaj-cy1xb2 жыл бұрын
Bro we need to download exercise from kaggle? As sir only uploaded image on github
@kalaipradeep275310 ай бұрын
I got 100% accuracy🎉🤩
@asitkmr4875 жыл бұрын
Very informative. As per my understanding LR model predicts the binary classification problem. It would be great if you can share how this predicts this multi class problem?
@codebasics5 жыл бұрын
Check machine learning tutorial playlist on my channel. I have example for binary classification as well and in fact this particular tutorial is for multiclass classification
@thannasip80013 жыл бұрын
Hi ,as you said sigmoid function will convert values to 0 or 1 ,how is it possible to predict digits with this concept ?,for binary output I got it but for digits it confused me
@ansh68482 жыл бұрын
I have set max_iter to 1,00,000 and achieved acurracy of 100%
@anandsingh10115 жыл бұрын
Your all video on any topic have deep theoretical explained with notebook , Can you suggest good resource or book for Machine Learning ?
@orangewares5 жыл бұрын
kzbin.info/www/bejne/hXjbmKF-bd5lhK8
@naveenkalhan954 жыл бұрын
@12:47 maybe not that important.. but just for my clarification, I would like to confirm... should plt.xlabel not be 'Truth' and plt.ylabel be 'Predicted' ? Thank you for your hard work.
@himanshugarg71134 жыл бұрын
Yes, it is. It has produced merely transpose.
@snehagupta-xz1fs3 жыл бұрын
even I've the same doubt
@jaiprathapgv22733 жыл бұрын
How can use this model used to recognize a new target image out of digits library?how to view the classification graph?
@musthakhahammed65352 жыл бұрын
I got 100% accuracy with 20% test size 😍😍😍 A big salute to this teacher