### 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. […]

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. […]

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 […]

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 […]

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 […]

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 […]

Linear Regression model in Python Sklearn part 1 [Polish Version] Jak uzupełnić brakujące dane w dataframe Python? Baza danych: AirQualityUCI Source of data: https://archive.ics.uci.edu/ml/datasets/Air+Quality In […]

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 […]

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]: Unnamed: […]

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 uempmed unemploy […]

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 […]

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 df = […]

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 numpy as np import seaborn as sns df […]

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