Open In Colab   Open in Kaggle

Intro#

Overview#

This is a bonus day on Autoencoders. Autoencoders are a form of deep neural network that performs nonlinear dimensionality reduction.

Install and import feedback gadget#

Hide code cell source
# @title Install and import feedback gadget

!pip3 install vibecheck datatops --quiet

from vibecheck import DatatopsContentReviewContainer
def content_review(notebook_section: str):
    return DatatopsContentReviewContainer(
        "",  # No text prompt
        notebook_section,
        {
            "url": "https://pmyvdlilci.execute-api.us-east-1.amazonaws.com/klab",
            "name": "neuromatch_cn",
            "user_key": "y1x3mpx5",
        },
    ).render()


feedback_prefix = "Bonus_Autoencoders_Intro"
  DEPRECATION: Building 'vibecheck' using the legacy setup.py bdist_wheel mechanism, which will be removed in a future version. pip 25.3 will enforce this behaviour change. A possible replacement is to use the standardized build interface by setting the `--use-pep517` option, (possibly combined with `--no-build-isolation`), or adding a `pyproject.toml` file to the source tree of 'vibecheck'. Discussion can be found at https://github.com/pypa/pip/issues/6334

  DEPRECATION: Building 'datatops' using the legacy setup.py bdist_wheel mechanism, which will be removed in a future version. pip 25.3 will enforce this behaviour change. A possible replacement is to use the standardized build interface by setting the `--use-pep517` option, (possibly combined with `--no-build-isolation`), or adding a `pyproject.toml` file to the source tree of 'datatops'. Discussion can be found at https://github.com/pypa/pip/issues/6334

ERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.
jupyter-server 2.13.0 requires jupyter-client>=7.4.4, but you have jupyter-client 7.3.5 which is incompatible.

Video#

Slides#

Submit your feedback#

Hide code cell source
# @title Submit your feedback
content_review(f"{feedback_prefix}_Video")