theibrr

# -*- coding: utf-8 -*-
"""
@author: Ibrahim Kovan
https://ibrahimkovan.medium.com/
"""
""" [1] """
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns

theibrr

"""
@author: Ibrahim Kovan
License CC0: Public Domain
https://ibrahimkovan.medium.com/
"""
import numpy as np
import matplotlib.pyplot as plt
import math
import pandas as pd
"1"

theibrr

"""
@author: Ibrahim Kovan
https://ibrahimkovan.medium.com/
"""

import numpy as np
import matplotlib.pyplot as plt
import math

X = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10]

theibrr

"""
@author: Ibrahim Kovan
https://ibrahimkovan.medium.com/
"""
from scipy.stats import poisson
import numpy as np
import matplotlib.pyplot as plt

X = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
lmbda = 4.6

theibrr

import matplotlib.pyplot as plt
from matplotlib.offsetbox import AnnotationBbox
from matplotlib import offsetbox
import tensorflow as tf
from sklearn.manifold import Isomap
from sklearn.datasets import fetch_openml
mnist = fetch_openml('mnist_784')
data = mnist.data[mnist.target == "9"][::10]

def plot_components(data, model, images=None, ax=None,

theibrr

import matplotlib.pyplot as plt
import numpy as np
from sklearn.datasets import load_digits
from sklearn.manifold import Isomap
from matplotlib.offsetbox import AnnotationBbox
from matplotlib import offsetbox
from sklearn.datasets import fetch_openml
from sklearn.datasets import fetch_lfw_people
faces = fetch_lfw_people(min_faces_per_person=40)

theibrr

import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
from sklearn.datasets import make_swiss_roll

X, color = make_swiss_roll(n_samples=1000, random_state=2021)

fig = plt.figure(figsize=(16,8))
ax = fig.add_subplot(111, projection='3d')
ax.scatter(X[:, 0], X[:, 1], X[:, 2], c=color, cmap=plt.cm.rainbow)

theibrr

import pandas as pd
import matplotlib.pyplot as plt
from sklearn.datasets import load_digits

digits = load_digits(n_class=5)
x, y  = digits.data, digits.target

def plot_digits(X,title):
    with plt.style.context(("seaborn", "ggplot")):
        colors = ['red','green','orange','blue','purple','cyan','magenta', 'firebrick','indigo']

theibrr

from sklearn.datasets import make_s_curve
import pandas as pd
import matplotlib.pyplot as plt

x, y = make_s_curve(n_samples=1000)


from sklearn.manifold import MDS
mds = MDS(n_components=2)
x_mds = mds.fit_transform(x)

theibrr

import seaborn as sns         
from matplotlib.offsetbox import OffsetImage, AnnotationBbox
import pandas as pd
import matplotlib.pyplot as plt
from sklearn.manifold import MDS


from sklearn.datasets import fetch_olivetti_faces
faces = fetch_olivetti_faces()
x_faces = faces.data