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. […]
Miesiąc: listopad 2019
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: Linear Regression – Time variables and shifts. Use of offset in variable correlation (#2/271120191334)
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) […]
Example of the use of shift for linear regression in Python. How to find optimal correlation shift?
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 […]
Perfect Plots: Combiplot
Feel free to read the code on GitHub Global market sales Source of data: https://github.com/vkrit/data-science-class/blob/master/WA_Fn-UseC_-Sales-Win-Loss.csv In [1]: import pandas as pd import matplotlib.pyplot as plt import […]