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https-deeplearning-ai/tensorflow-1-public

https-deeplearning-ai
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h93xV2
h93xV2
Asked: September 18, 2023, 6:28 pm
Issue

Typo in C4_W4_Lab_3_Sunspots_CNN_RNN_DNN

  • 000
In the C4_W4_Lab_3_Sunspots_CNN_RNN_DNN notebook, there's a small typo. It says: As mentioned in the lectures, if your results don't good, you can try tweaking the parameters here and see if the model will learn better. The part which doesn't look right is don't good. I'm not sure what the author...
  • 0 0 Comments
OPEN
holleyism
holleyism
Asked: August 7, 2023, 3:13 am
Issue

Minor typo in C4_W2_Lab_3_deep_NN.ipynb

  • 000
In the 3rd to last markdown cell, the fifth word is missing a letter. Alternatively, the typo appears on line 696 of the raw ipynb file. You can get the preictions again and overlay it on the validation set. should be: You can get the predictions again and overlay it on the validation set.
  • 2 2 Comments
OPEN
xyashapyx
xyashapyx
Asked: July 15, 2023, 11:46 am
Issue

C2_W4_Lab_1_multi_class_classifier.ipynb No module named 'keras_preprocessing'

  • 000
In the "Prepare the ImageDataGenerator" it is needed to replace "from keras_preprocessing.image import ImageDataGenerator" with "from tensorflow.keras.preprocessing.image import ImageDataGenerator" without this I'm getting the error: `-----------------------------------------------------------------...
  • 1 1 Comments
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abhiseketan5
abhiseketan5
Asked: March 9, 2023, 11:24 am
Issue

C1_W2_Lab_1_beyond_hello_world.ipynb Error in tf.keras.activation.softmax

  • 000
input to softmax function: [1. 3. 4. 2.] ValueError Traceback (most recent call last) ~\AppData\Local\Temp\ipykernel_21880\3343928682.py in 5 6 #feed the inputs to a softmax activation function ----> 7 outputs = tf.keras.activations.softmax(inputs) 8 print(f'output...
  • 1 1 Comments
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nwipfli
nwipfli
Asked: January 12, 2023, 6:31 am
Issue

Small correction in the ReLU explanation

  • 000
I think the following sentence: In other words, it only passes values 0 or greater to the next layer in the network should be updated as below: In other words, it only passes values greater than 0 to the next layer in the network Because the test is: if x > 0: return x
  • 1 1 Comments
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el-dAna
el-dAna
Asked: November 1, 2022, 1:15 pm
Issue

Typo

  • 000
At, 'Build the model' second paragraph line 5. "For the input_shape, you can specify None (like in the lecture video) if you want to be the model to be more flexible with the number of timesteps."
  • 1 1 Comments
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ayanatherate
ayanatherate
Asked: October 12, 2022, 6:26 pm
Issue

TypeError: '<' not supported between instances of 'NoneType' and 'float' while using callbacks to stop training after a certain mae

  • 000
Code for W4 Time Series Notebook on using a callback to stop training after a certain mae model: LSTM class myCallback(tf.keras.callbacks.Callback): def on_epoch_end(self, epoch, logs={}): ''' Halts the training when a certain metric is met Args: epoch (integer) - index of epoch...
  • 1 1 Comments
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hiroshiichise
hiroshiichise
Asked: October 1, 2022, 11:00 pm
Issue

C2W1_Assignment.ipynb: Expected Output is wrong

  • 000
The number of images should be 12500, not 12501 Expected Output: There are 12501 images of dogs. There are 12501 images of cats. In the Dog and Cat directory in the Zip there are 12501 files. However, after extracting the Zip to tmp, Thumbs.db is deleted by under code, so the file count is 12500....
  • 1 1 Comments
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eavelardev
eavelardev
Asked: September 26, 2022, 7:40 pm
Issue

C3W1_Assignment.ipynb: wrong remove_stopwords implementation

  • 000
The notebook mention you should get a vocabulary that contains 29714 words, but that vocab still contains stop words. That's because a basic implementation of remove_stopwords just removes the stop words without consider that ones with punctuation as a part of the word. So if there is a word in a se...
  • 1 1 Comments
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rediet-orange
rediet-orange
Asked: August 19, 2022, 7:59 am
Issue

C1_W2_Lab_1_beyond_hello_world.ipynb: some portions still tailored for mnist dataset

  • 000
In the exploration exercises some portions are still pertaining to mnist, instead of fashion_mnist. mnist = tf.keras.datasets.mnist -&gt; mnist = tf.keras.datasets.fashion_mnist Exercises 2, 4, 5, and 7: no impact on the global meaning, just for consistency Exercise 3: the dimensions in the error...
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