gitgithan

Failed pip install -r requirements.txt, rasa train, rasa shell

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After `pip install -r requirements.txt` ``` ERROR: Cannot install -r requirements.txt (line 6) and rasa[spacy]==3.1.0 because these package versions have conflicting dependencies. The conflict is caused by: rasa-sdk 3.1.0 depends...

Errors doing `make install`

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I'm trying to setup rasa-demo on python 3.7.13 in a pyenv-virtualenv on macOS Big Sur non-M1. If I just do `make install`, it will be a very slow install process...

From Datacamp's "Machine Learning with the Experts: School Budgets" 2.Creating a simple first model -Setting up a train-test split in scikit-learn, the lesson text says > "Some labels don't occur...

The ebook was so repetitive. I'm curious if it was written by gpt, was it done programmatically feeding lists of prompts and how is that done.

There was a tip >The LinearSVC class regularizes the bias term, so you should center the training set first by subtracting its mean I couldn't find any resource discussing why...

index.xb no such attribute

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In the section `std::vector to/from np.array`, index.xb is used but this attribute no longer exists. A newer example using `index.get_xb()` works (https://github.com/facebookresearch/faiss/issues/2266#issuecomment-1072315659) However I'm not clear why the 2nd parameter...

chapter-4/1_feature_extraction.ipynb using default batch size 32 instead of defined batch_size 128

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``` batch_size = 128 datagen = tensorflow.keras.preprocessing.image.ImageDataGenerator(preprocessing_function=preprocess_input) generator = datagen.flow_from_directory(root_dir, target_size=(224, 224), class_mode=None, shuffle=False) ``` uses default batch_size = 32. `num_epochs = int(math.ceil(num_images / batch_size))` calculates 68 epochs based on...

chapter-4/2-similarity-search-level-1.ipynb Broken float division

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``` def plot_images(filenames, distances): images = [] for filename in filenames: images.append(mpimg.imread(filename)) plt.figure(figsize=(20, 10)) columns = 4 for i, image in enumerate(images): ax = plt.subplot(len(images) / columns + 1, columns,...

3 changes in this notebook to fix #163 #164 1. Quoting paths to prevent zsh shells erroring with `zsh:1: no matches found: https://drive.google.com/uc?id=137RyRjvTBkBiIfeYBNZBtViDHQ6_Ewsp` because it treats ? as glob character....

chapter-4/4-improving-accuracy-with-fine-tuning.ipynb does not contain the final finetuning section that is in book

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There is a final finetuning throwing away dense and dropout layers that was expected according to the book but is missing in the notebook