TensorFlow Tutorial For Beginners | Deep Learning with Python

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In this TensorFlow tutorial for beginners, we will perform deep learning with python. By the end of this deep learning tutorial you will have written your first neural network that can recognize hand written digits with the mnist dataset. We will start by importing the necessary libraries, then we will download the mnist dataset. After splitting the dataset to training and test datasets we will scale their pixel values to a range our neural network can work easier with. Then we will build, train, evaluate, save and retrieve our neural network model. I hope you got some value out of it. If you have any suggestions comment them down below.
If you learn better by reading, I have an article version of this tutorial, with all the code included:
/ write-your-first-ai-pr...
Google Colab:
colab.research...
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Опубликовано:

27 сен 2024

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Комментарии : 24

@eliotttessier112 2 года назад

for me, perfect introduction to tenserflow/keras.

@eastcoastofzanzibar2465 Год назад

Well done,,, Short tutor and clear codes presentation,,, And is useful,,,,! Thanks,,,!

@ronymora1371 3 года назад

Great explanations. I am new on this and this video helped me a lot. Thank you very much.

@hackercop 3 года назад

Wow you are a good tutor this video was helpful, if you persevere with these videos YT algorithm will reward you.

@DogaOzgon 3 года назад

Glad it was helpful!

@AstralTraveler Год назад

Hello! Everything worked perfectly up until 9:37 When I run the script I get the message: :12: SyntaxWarning: 'int' object is not subscriptable; perhaps you missed a comma? :12: SyntaxWarning: 'int' object is not subscriptable; perhaps you missed a comma? :12: SyntaxWarning: 'int' object is not subscriptable; perhaps you missed a comma? my_model.compile(optimizer='adam', loss='sparse_categorical_crossentropy', metrics=1['accuracy']) --------------------------------------------------------------------------- TypeError Traceback (most recent call last) in 10 metrics=[tf.keras.metrics.BinaryAccuracy(), 11 tf.keras.metrics.FalseNegatives()]) ---> 12 my_model.compile(optimizer='adam', loss='sparse_categorical_crossentropy', metrics=1['accuracy']) 13 14 # train the model TypeError: 'int' object is not subscriptable

@Gowtham25 3 года назад

All your teaching stuffs are really good and in a easily understandable way!. Keep on rock and create a more videos about A.I & M.L. like this.

@DogaOzgon 3 года назад

Thanks, will do!

@TruthOfZ0 3 года назад

i dont understand what each line of the code you type does... is there a flow diagram behind all this?

@zwitter689 2 года назад

Very nice explanation - is it possible to get a transcript of this?

@jedigunn Год назад

Thank you so much for the great content.

@chaaaaaaaaaaan 10 месяцев назад

Pretty late to this vid but thanks a lot. Learnt a lot from you today!

@harjasdeepsingh6550 3 года назад

Keep posting new videos on machine learning and deep learning

@oliversimmons988 2 месяца назад

love it. Great video

@maxkosh4839 2 года назад

ok. How to use this model???

@fidlekid 10 месяцев назад

my_model.predict(np.array([test_images[0]])) and then check which index has the highest value

@pankajpanchal4431 2 года назад

im getting File "", line 7 plt.imshow(train_images[1]), cmap='gray') ^ SyntaxError: invalid syntax kindly help

@romanborisov348 2 года назад

the bracket after "train_images[1] is causing the error, because you now have one opening bracket and two closing brackets

@MahRahman1 Год назад

impressive

@alevera16 2 года назад

Thank you!!

@suparnabhattacharya3524 3 года назад

Keep up the good work. Your video was really very helpful.

@MyFirstReurveBow Месяц назад

no one can learn anything from that. you just load random data, no one actually want this for a random data the point is to learn how to use your own..