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...

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

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."

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...

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....

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...

In the exploration exercises some portions are still pertaining to mnist, instead of fashion_mnist. mnist = tf.keras.datasets.mnist -> 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...

The below section of the lab notebook " C3_W2_Lab_1_imdb.ipynb" causes Value error: Code num_epochs = 10 # Train the model model.fit(padded, training_labels_final, epochs=num_epochs, validation_data=(testing_padded, testing_labels_final)) Error: 774/782 [============================>.] - ETA: 0...

How do I fix the following error? It happens when I try to run the final codeblock where you have to call the function. Please help, I'm kinda stuck here --------------------------------------------------------------------------- AttributeError Traceback (most recent call...

seed_text = "Laurence went to dublin" next_words = 100 for _ in range(next_words): token_list = tokenizer.texts_to_sequences([seed_text])[0] token_list = pad_sequences([token_list], maxlen=max_sequence_len-1, padding='pre') predicted = model.predict_classes(token_list, verbose=0) output_word...