Transfer Learning | Deep Learning Tutorial 27 (Tensorflow, Keras & Python)

📺 Transfer learning is a very important concept in the field of computer vision and natural language processing. Using transfer learning you can use pre trained model and customize it for your needs. This saves computation time and money. It has been a revolutionary break through in the field of deep learning and nowadays you see it being used widely in the industry. In this video we will go over some theory behind transfer learning and then use google's mobile net v2 pre trained model to train our flowers dataset
#transferlearning #transferlearningdeeplearning #transferlearningkeras #transferlearningtensorflow #transferlearningmodels #deeplearningtutorial #transferlearningexample
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❗❗ DISCLAIMER: All opinions expressed in this video are of my own and not that of my employers'.

[@codebasics]

Do you want to learn technology from me? Check codebasics.io/ for my affordable video courses.

[@sherifbadawy8188]

Man your courses taught me to lose my ego, and to live out for the people. Thank you so much for this. This has to be a blessed deed that you did this.

[@AlonAvramson]

Your way of explaining complex issues in such an easy and simple way is truly amazing. Thank you!

[@sandiproy330]

With a clear example you explained transfer learning so beautifully. LOved to see your tutorial. Thank you so much sir.

[@zaidalmahmoud4272]

Wow! What a simple and clear illustration of Transfer Learning. Thank you!

[@bhaskargg6018]

no words to praise, the session is superb , thanks a lot for sharing your knowledge

[@GautamKumarBEE]

A very humble request, please add atleast 5-6 more videos in this series.

[@mums2109]

Even though this of two years old it is still very well taught. Thank you!

[@mhdkfl]

By watching your deep learning whole series i have cleared my bunch of doubts . Your way of putting any topic so simple is really amazing. Hatts off to your teaching methodology. A heartiest request to you to Please upload NLP series (including LSTM and Encoders/Decoders) with a good project. I am eagrely waiting.

[@codebasics]

Yes nlp series is in my plans

[@zkhan2023]

@@codebasics sir, when will you starting that series?

[@bagheerathan8975]

here how can we test the model after train the model plz tell me

[@bagheerathan8975]

@@codebasics here how can we test the model after train the model plz tell me

[@homeOfTrivia]

Excellent course. This is my "Go To" resource for Machine Learning and Deep Learning. Please think of creating a series of projects that can make one grow their skills. Keep the price affordable.

[@work-dw2hl]

Your teaching style is outstanding

[@anoshpa-6531]

I don`t have words to thank you for this deep learning series, you have explained every single topic in simple language. Thanks a ton :) :) Keep Uploading such series :)

[@codebasics]

👍☺️

[@bagheerathan8975]

here how can we test the model after train the model plz tell me

[@prajjowldahal8959]

@@codebasics sir in github code are not there it shows error it is moved from github????

[@shreyasb.s3819]

Omg..u have cleared my lot of doubts here...superbbb explained...thank you much sir. Please contribute more towards RNN also like this.

[@codebasics]

Sure I will

[@sumit121285]

really helpful....you are the best teacher for deep learning....also for machine learning.....thankyou so much...... i m a big fan of yours.....

[@codebasics]

😊🙏

[@izharkhankhattak]

Really great lecture. Keep helping the people like that. Thank you so much.

[@codebasics]

My pleasure

[@bagheerathan8975]

@@codebasics here how can we test the model after train the model plz tell me

[@pratyushsinha5201]

Thank you so much sir. This was extremely helpful!

[@codebasics]

Glad it helped!

[@arcanepersona1676]

Thanks a lot , I appreciate your way of explaining deep learning 😊 I would like to ask about image classification using transfer learning .. if I have a dataset of images with the size 100x100 .. and the image size in the pre trained model is 300x300 .. a bigger size .. how do I make my smaller sized original images fit in that pre trained model ?

[@inhibited44]

That example with the flower identified as an umbrella got me thinking. I applied your model to my data. I have pictures of an object with rust and blemishes on them. The model identified a few pictures as a snake of some sort or a hyena. If I do a case study of a bunch of pictures in my data and feed them to the model, I should be able to program into it the actual appropriate identity once the model has ascertained it's a snake, hyena or whatever.

[@harshalbhoir8986]

This is something new I learned!!!

[@akshayvasav2497]

@codebasics this is greatest video of transfer learning i have ever seen, usually people load dataset from tensorflow directly instead of local disk. You load it from local disk which is great thing. I just have one question what you appended in "y" , class name or class Id ?

[@srishtikumari6664]

Wonderful explanation!!

[@bensalah90]

nice video keep going ;so what would you suggest as model from TL HUB to train signal or spectogram

[@tomdapchai]

thanks, very easy to follow

[@ansariarbaz3374]

nice video sir just wanna add u must use softmax activation function in last layer directly.... please

[@tewodrosgebre204]

Thank you. Helpful.

[@nguyennhi8524]

Thank you so much!!! 👏

[@HotshotArafath]

Sir can we use this method for the leaf disease project also as a extension?

[@nineteen5899]

Thanks mate... it helped.. Love from London..

[@codebasics]

Glad it helped

[@sagarmahobia5159]

Wouldn't it affect the ability to recognize images other than these flowers because now the last layer has been trained with a smaller dataset? Like recognizing a chair or. bike

[@dileeppanigrahi4453]

Hi sir, How can i remove the last layer , without using feature_vector model. what i mean is how to remove the last layer from the classification model(mobilenet_v2) and freeze the trained layers .

[@fvviz409]

Hey can you teach us how to do real time neural network prediction using open-cv? It is very useful in computer vision

[@ucm269]

In the last layer of the trained model, though softmax layer is being used , how we are getting some of our prediction values to be greater than 1??

[@tirthadatta7368]

Sir, the tutorial is well made. But can u please tell us how to add batch size and other preprocessing steps in this code??

[@pvtgcn8752]

Very Lucid Explanation

[@saltanatkhalyk3397]

Thank you very much.

[@codebasics]

Glad it was helpful!

[@suhaalam2127]

Do you have any tutorial where u have shown any regression problem solving using deep learning?

[@sanooosai]

thank you sir

[@adityahpatel]

Hello, why are there so many MobileNet model variants on Tensorflow hub? Like mobilenet_v2_50_192, mobilenetv2_035_96, mobilenetv3_large_100_224 and so many other variants? What is the different between these?

[@navneetkumar5517]

thank you so much bhaiya

[@aninditasaha0307]

Sir... Can you please show CNN in UCIHAR dataset... Will be really helpful

[@andrewzolensky9807]

Hi, great tutorial! Quick question, when training the single dense layer around minute 24:00, why is there no activation function (e.g. softmax) applied to the final, trainable dense layer?

[@andrewzolensky9807]

Edit: minute 23:30

[@gauravtripathi562]

It's taking by default value for that and its relu i think or you can check....but keeping it empty means it's taking default value for that

[@yassmingourya9975]

Hey, I really liked your videos you are explaining everything in a quiet simple way, but can we use transfer learning on non_image data set? , like I have a dataset composed of srtings I transformed it to arrays and I want to make predictions using arrays, does transfer learning help in this case? Thanks a lot

[@codebasics]

yes transfer learning is not restricted to only images. you can use it for other problems too

[@yassmingourya9975]

@@codebasics ah great, thanks for your reply. please can you help with some documentations or instructions on how to do i'll be so grateful

[@sanarabhi4906]

@@yassmingourya9975 please did you found documentations for using transfer learning on non_image data set , i need to do it but can't find anything useful. thank you

[@Raj-sz9pg]

from where did you downloaded those classes list ?

[@Janamejaya.Channegowda]

Thank you, can transfer learning be done for time series data?.

[@chymoney1]

Yes, but I’d imagine it does not have advantages over LSTM or transformer

[@siddharthkshirsagar2545]

amazing🙃

[@kollurisharada5102]

VERY GOOD EXPLANATION

[@codebasics]

Thanks for liking

[@advertisemedia1509]

can you show how prediction is done after transfer learning is done .... i mean after retraining the model with flower images plz show how to check results... thanks a lot... i tried but couldn't do ....thanks a lot

[@zaindurani8168]

Thanks a lot sir

[@codebasics]

👍😊

[@rahulrangu6506]

hi sir can we get the ppt also in deep learning tutorials and Machine Learning tutorials that you have used to explain the concepts

[@juangutierrez3309]

YOU ARE A LEGEND! Thanks for helping me understand how transfer learning worksQ Just had one question... I understood everything but this piece of code: model.compile( optimizer="adam", loss=tf.keras.losses.SparseCategoricalCrossentropy(from_logits=True), metrics=['acc']) Where did you get this? Do I use this with any model I use for transfer learning?

[@codebasics]

This has nothing to do with transfer learning. Whenever you train a model in deep learning you need to use this line

[@bagheerathan8975]

here how can we test the model after train the model plz tell me

[@bagheerathan8975]

@@codebasics here how can we test the model after train the model plz tell me

[@naa12333]

thank you sir for the wonderful tutorials... I am following all the steps in this video as well in previous episode (26), I get an error when I train the model, since I am new I could not figure out how to fix this error. error: ValueError: Data cardinality is ambiguous: x sizes: 2752 y sizes: 918 Make sure all arrays contain the same number of samples.

[@sabarimahesh]

Is it possible to do transfer learning for ANN ? Any reference available ? I could see more examples for CNN. Is there any reason behind.

[@UsmanKhan-hu8hw]

can we apply the same way for transforming of text sentiment model?

[@jrajpal5]

Hi sir, i watch your videos every day But with the same dataset, i am getting losses of 1.6 and accuracy close to 0.21 with transfer learning as well as with cnn So please tell how can i improve them

[@SachinGupta-dn7wt]

You predicted using a classifier that was pre-trained(in which you got inaccurate results), but I wanted to see how we can give one input image and check the output by using the new classifier.

[@harshitrathi3077]

sir is the python project of Grocery Application Completed ?

[@reinishasarojini6908]

I need more videos on transfer learning sir

[@abduladhilpk8223]

why yolo algorithm takes hours to train to perform object detection using transfer learning

[@nastaran1010]

the model perfomance with useing 'feature vector' is increased. but when i tried to predict ([X[0],X[1], X[2]]), it perfomes so bad. why?

[@dilipkumar2k6]

You need a standing ovation :-)

[@RanjitSingh-rq1qx]

Sir please make more videos on transferring learning.i think this is not sufficient to use transferring learning in more easy way 🙏

[@balajim2107]

It shows flowers as umbrella and so on..Then using mobilenet is good?or bad?

[@Frostbyte-Game-Studio]

holy fuck that might save me a lot of fucking trouble thank you so much for this video and for this code

[@rahaf1418128]

is this could consider as convolutional neural network?

[@chealsytchasso3871]

HI is it possible tu convert an image of 3D dimensions in to an image of 4D dimensions?

[@HIMANSHU-lm5tg]

sir, u have taught so much of free that i have not learnt in any of the paid courses. i am trying to use ML and AI in financial instruments for trading and investing. but due to non familiarity with ML and AI world I m not able to figure out from where to start and what is relevant for me. plz guide me.

[@saarakauser7008]

very informative sir. can you explain how to combine 2 or more pretrained models..

[@aintthatharsh]

How and why would someone do that?

[@yashu1089]

which classifier are you using

[@saltanatkhalyk3397]

your code works ^_^

[@nastaran1010]

what is the version od tensorflow, hub?

[@praneedhaweerakoon8570]

What are the methods available to improve the accuracy of custom models??except trial and error.

[@zaindurani8168]

Keras tuner try it

[@user-ez2lb5um4x]

sir, how to search TensorFlow hub training models give me the same as you have used.

[@drotta45]

why we didn't use an activation function in last dense layer ?

[@kunalll24]

Having error while using the pretrained model, error : ValueError: Only instances of `keras.Layer` can be added to a Sequential model. Received: (of type ) please help.

[@rasanjalirathnayake8873]

when we use pupil detection, i mean wha t I need is to localize the pupil center, are we using classification? just like left eye and right eye ? or something else? please reply.

[@codebasics]

Are you doing object detection? Have you tried yolo etc?

[@gokkulkumarvd9125]

sir, how many more videos will be there?

[@charantejchetty149]

Hey , how can I download Mobile net V2 dataset?

[@321-youvrajsinghgaur3]

Please Tell How can we save this model after transfer learning !

[@Maryashahere]

Sir how can we apply transfer learning for numerical data?

[@Makingrobloxvids]

hello how can I use Transfer learning on 1 dimension data

[@Raj-sz9pg]

how to know if its working? in the end after we run 5 epoch

[@riadelectro1]

Please teacher; could you give me a master topic proposal about clustering images?

[@krutikagouda2696]

Can you please suggest trained model for ai based picture translation project

[@quattrandang4312]

Hello guy ! I need help . Specifically, I followed your code but when I bring that model to deploy in my project, using load_model does not work. Ok i understand it doesn't save the complete model but i want it to save only the part i changed (output layer) so when i use it i need to have it (custom_objects={'KerasLayer':hub.KerasLayer }) . But the problem here is that when I use the above command, my model will not work after a period of time (according to my understanding, when I load the model in the above way, it will download a temporary folder containing the information. the model number and structure ( which contains some .pb and pbtxt files ) - this folder will be partially deleted by something after about a week , so it causes an unusable error , If you want to use it again, you need to delete the folder and let it download the new one). I don't want my program to crash every once in a while. Do you have any way ? In addition, I have found a way to fix it, but it is not a good way. I use :" from tensorflow.keras.applications import " to load sample models and add classes directly to this model. It works like a self-built model so you don't have to reload the keras layer every time you use it (which caused my error). However, this way it is quite resource-intensive. Do you have a better alternative? Thanks for reading . Looking forward to hearing from you soon.

[@dr.md.atiqurrahman2748]

Wow!!!!!!! If I had an option, I would subscribed (1000000000000000000000000000....................I don't know how many zeros I would add) times.

[@codebasics]

Thanks for your kind words of appreciation Atiqur.

[@snehashrivastav5544]

Can you please add the fish dataset link

[@vaishnavip2327]

Can I get the documentation you refered for mobile v2 net architecture ? I have used the code , so it would be helpful to get explanation of the architecture

[@HotshotArafath]

Did you got?

[@vaishnavip2327]

@@HotshotArafath nope

[@studentmitra5372]

Can you please analyse HAM10000 dataset. Because this dataset is highly imbalanced and it also contain meta data in csv file. So I am bit confused.

[@studentmitra5372]

it's humble request

[@baburamchaudhary159]

since, we have 1000 classes, why do we get (1, 1001), when executing result.shape

[@arpitjain6451]

model.fit(X_train_scaled, y_train, epochs=5) ValueError: Failed to convert a NumPy array to a Tensor (Unsupported object type list). error occur at this line

[@anshXR]

model.fit only accept numpy arrays. So try running this :- X_train_scaled = np.array(X_train_scaled) y_train = np.array(y_train)

[@user-tr2sm3sw4b]

how to increase running speed of epoch in jupyter notebook for flower dataset classification

[@hafizhtrinelzy145]

buy gpu instead

[@amudalagopikrishna5745]

what is that third value in the input shape

[@huskymotivations]

it mean the images are color images, like (RGB), and if we have black and white images we use 1 instead of 3. I'm also a beginner but i guess most probably that's the reason

[@nareshagarwal8243]

can you please also add a video on NLP?

[@codebasics]

Yes the RNN tutorials are coming up from tomorrow. First one will be uploaded tomorrow (Tuesday) 7 pm IST

[@Abhishek-jd9qk]

What was the need of adding 1 and 3 to the dimensions ?

[@lakshsinghania]

same doubt, maybe the index/number

[@tickokok1410]

while i am running classifier.preduction it's showing your kernal is dead

[@tickokok1410]

please let me know the solution

[@uswakhan3050]

can anyone help me in resolving this error .... ValueError: Only instances of `keras.Layer` can be added to a Sequential model. Received: (of type )

[@parimalkothari7607]

Got the solution?

[@wildkaziranga]

Sir, Please help me, how to make auto segregation wild animal photographs of python coding . I m from Kaziranga National Park.

[@highspeedhiasl]

can you please make me 34b with spicy?

[@chathuranj2825]

I am working on a skin disease detection problem, I would like to know if you give me suggestions on how to increase the accuracy. Its because I have been trying to increase the accuracy yet it is stuck at 60%

[@chathuranj2825]

Also can you please suggest any good dataset for skin disease detection. It shouldn't be the usually cancer dataset, rather a set of maybe 8-9 diseases prominent in India

[@dr.md.atiqurrahman2748]

I can not believe that this video tutorial series can get dislike. Watch the videos well, I am 100% sure you will covert your thinking from dislike to like.