关于“Inspecting a Dataset for Bias using TensorFlow Data Validation and Facets Overview”的评价

Prakhar K. · 已于 over 1 year前审核

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Geetha S. · 已于 over 1 year前审核

Jupyter notebooks pip install package too slow?

Huy M. · 已于 over 1 year前审核

not user friendly, needs more elaborate instructions on Task 4

Hemali P. · 已于 over 1 year前审核

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MADHURANK H. · 已于 over 1 year前审核

Chaitali S. · 已于 over 1 year前审核

good one

Rakesh S. · 已于 over 1 year前审核

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Swathi D. · 已于 over 1 year前审核

Ravindra S. · 已于 over 1 year前审核

TL;DR 1. Unable to run module because dependancies failed to install correctly. 2. User is not provided with the URLs for the preprocessed training and validation datasets in exercise "TODO 1". 3. User is expected to be familiar with the tf.keras utility functions and syntax. DETAILS: 1. When installing the dependancies, after installing the Fairness indicators and restarting the kernel, I received the following error: --------------------------------------------------------------------------- ModuleNotFoundError Traceback (most recent call last) Cell In[1], line 13 11 import tensorflow_hub as hub 12 import tensorflow as tf ---> 13 import tensorflow_model_analysis as tfma 14 import tensorflow_data_validation as tfdv 15 from tensorflow_model_analysis.addons.fairness.post_export_metrics import fairness_indicators ModuleNotFoundError: No module named 'tensorflow_model_analysis' #END OF ERROR MESSAGE This effectively prevented me from continuing this lab. 2. For the "TODO 1" exercise the location of the preprocessed training and validation datasets was not called out anywhere in the Jupyter Notebook or elsewhere in the documentation. I was forced to inspect the "bias_tfdv_facets.ipynb" file to find the file location URLs. Due to the aforementioned "ModuleNotFoundError", I was unable to complete the "TODO 2" exercise and received the following error: --------------------------------------------------------------------------- NameError Traceback (most recent call last) Cell In[3], line 4 1 # TODO 2 2 3 # The computation of statistics using TFDV. The returned value is a DatasetFeatureStatisticsList protocol buffer. ----> 4 stats = tfdv.generate_statistics_from_tfrecord(data_location=train_tf_file) 6 # TODO 2a 7 8 # A visualization of the statistics using Facets Overview. 9 tfdv.visualize_statistics(stats) NameError: name 'tfdv' is not defined 3. In order to complete any of the "TODO" exercises without consulting the answer cheat sheet, the user is expected to be familiar with the tf.keras utility functions and syntax, which is an entire language in and of itself.

William V. · 已于 over 1 year前审核