From 45191cb7abb85e8fabdea2c6d67bcdbea1bdcc00 Mon Sep 17 00:00:00 2001 From: Leland McInnes Date: Sat, 19 Oct 2024 09:15:02 -0400 Subject: [PATCH] Update MNIST_Landmarks.ipynb per AMS suggestions --- notebooks/MNIST_Landmarks.ipynb | 11 ----------- 1 file changed, 11 deletions(-) diff --git a/notebooks/MNIST_Landmarks.ipynb b/notebooks/MNIST_Landmarks.ipynb index ca220528..1e3c1468 100644 --- a/notebooks/MNIST_Landmarks.ipynb +++ b/notebooks/MNIST_Landmarks.ipynb @@ -10,16 +10,6 @@ "UMAP is useful for generating visualisations, but if you want to make use of UMAP more generally for machine learning tasks it is important to be be able to train a model and then later pass new data to the model and have it transform that data into the learned space. For example if we use UMAP to learn a latent space and then train a classifier on data transformed into the latent space then the classifier is only useful for prediction if we can transform data for which we want a prediction into the latent space the classifier uses." ] }, - { - "cell_type": "code", - "execution_count": 1, - "id": "464ec109-f662-4201-8c77-ea7f87beb5a3", - "metadata": {}, - "outputs": [], - "source": [ - "!pip install keras scikit-learn umap-learn matplotlib numpy pandas" - ] - }, { "cell_type": "code", "execution_count": 2, @@ -50,7 +40,6 @@ "import matplotlib.pyplot as plt\n", "\n", "import numpy as np\n", - "import pandas as pd" ] }, {