Zabezpieczone: TENSORFLOW LINE CLASSIFICATOR (base example)
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Publikacje internetowe
TensorFlow — obliczanie R-kwadrat dla regresji liniowej
Parking Birmingham occupancy Source of data: https://archive.ics.uci.edu/ml/datasets/Parking+Birmingham In [35]: import pandas as pd df = pd.read_csv(’c:/TF/ParkingBirmingham.csv’) df.head(3) Out[35]: SystemCodeNumber Capacity Occupancy LastUpdated 0 BHMBCCMKT01 577 61 […]
Cz. 1. Poprawa modelu regresji liniowej za pomocą zmiennych syntetycznych
EN031220191208 Parking Birmingham occupancy analysis Source of data: https://archive.ics.uci.edu/ml/datasets/Parking+Birmingham In [1]: import pandas as pd df = pd.read_csv(’c:/TF/ParkingBirmingham.csv’) df.head(3) Out[1]: SystemCodeNumber Capacity Occupancy LastUpdated […]
Polynomial regression model
Polynomial regression model Polynomial regression model is technically a special case of multiple linear regression. This is definitions and explanation found in Wikipedia: https://en.wikipedia.org/wiki/Polynomial_regression. Just […]
Tutorial: Linear Regression – Sklearn regression model (#3/281120191333)
In the previous part, we tried to build a model by trying to explain the level of carbon monoxide pollution based on temperature and pressure. […]
Tutorial: Linear Regression – Tensorflow, calculation of R Square (#4/281120191525)
We continue to learn how to build multiple linear regression models. This time we will build a model using the Tensorflow library. As before, the […]
Tutorial: Linear Regression – preliminary data preparation (#1/271120191024)
Part 1. Preliminary data preparation AirQualityUCI Source of data: https://archive.ics.uci.edu/ml/datasets/Air+Quality In [1]: import pandas as pd df = pd.read_csv(’c:/TS/AirQualityUCI.csv’, sep=’;’) df.head(3) Out[1]: Date […]
Tutorial: regresja liniowa — zmienne czasowe i przesunięcia. Wykorzystanie przesunięcia w korelacji zmiennych
Part 2. Simple multifactorial linear regression In the previous part of this tutorial, we cleaned the data file from the measuring station. A new, completed […]
Linear regression with TensorFlow
Part one: Numpy method In [1]: import pandas as pd import tensorflow as tf import itertools Source of data: https://archive.ics.uci.edu/ml/datasets/combined+cycle+power+plant Combined Cycle Power […]
Jak uzupełnić brakujące dane w dataframe Python?
Jak uzupełnić brakujące dane w dataframe Python? Baza danych: AirQualityUCI Source of data: https://archive.ics.uci.edu/ml/datasets/Air+Quality In [47]: import pandas as pd df = pd.read_csv(’c:/TS/AirQualityUCI.csv’, sep=’;’) df.head(3) […]
Przykład użycia przesunięcia w regresji liniowej w Pythonie. Jak znaleźć optymalne przesunięcie korelacji?
What is this the correlation shift? In supervised deep machine learning we have two directions: classification and regression. Regression needs continuous values of data. Because […]
Perfect Plots: Bubble Plot
In [1]: import pandas as pd import matplotlib.pyplot as plt import numpy as np Autos Source of data: https://datahub.io/machine-learning/autos In [2]: df2= pd.read_csv(’c:/1/autos.csv’) df2.head() Out[2]: […]
Perfect Plots: Subplots
In [1]: import pandas as pd import matplotlib.pyplot as plt import numpy as np Economics In [2]: df=pd.read_csv(’c:/1/economics.txt’) df.head() Out[2]: date pce pop psavert […]
Perfect Plots: Individuals Control Chart I-MR
Energy Source of data: https://github.com/pyviz/holoviews/blob/master/examples/assets/energy.csv In [1]: import pandas as pd import matplotlib.pyplot as plt import numpy as np In [2]: df=pd.read_csv(’c:/2/Energy.csv’) df.head() Out[2]: Unnamed: 0 Date […]
Perfect Plots: Bar plots
In [1]: import pandas as pd import matplotlib.pyplot as plt import numpy as np import matplotlib.patches as mpatches Car statistics In [2]: # Prepare Data […]