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This ipynb is based on a workshop organised by the tech consulting company TNG. The notebook explains the theoretical background of three widely used clustering algorithms and uses them on some sample data. As a final example, clusters are used to ‘‘discretise’’ the colours of an image.
import numpy as np import seaborn as sns import matplotlib import matplotlib.pyplot as plt #from plotting_utilities import * from sklearn.datasets import make_moons, make_blobs from sklearn.
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Based on this tutorial by pavithrasv
This notebook demonstrates how you can use a reconstruction convolutional autoencoder model to detect anomalies in timeseries data. First we import tensorflow and other relevant packages.
import numpy as np import pandas as pd from tensorflow import keras from tensorflow.keras import layers from matplotlib import pyplot as plt 2022-09-28 12:22:09.199724: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations: AVX2 FMA To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.