Category : Scikit-learn

How to avoid overfitting in deep learning with regularizer and drop out?

     AI, Data, Deep Learning, Keras, Machine Learning, Numpy, Pandas, Python, Scikit-learn, Worknotes

beautiful sprawling fantasy vast landscape

Sample code for reducing overfitting problems in deep learning.Answer the following questions: import numpy as np import pandas as pd from sklearn.model_selection import train_test_split from sklearn.preprocessing import StandardScaler # create range of monthly dates download_dates = pd.date_range(start=’2019-01-01′, end=’2020-01-01′, freq=’MS’) # URL from Chrome DevTools Console base_url = (“https://climate.weather.gc.ca/climate_data/bulk_data_e.html?format=csv&” “stationID=51442&Year={}&Month={}&Day=7&timeframe=1&submit=Download+Data”) # add format option to year ..

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How to construct a regression model with Keras with more than two input layers?

     AI, Data, Keras, Numpy, Pandas, Python, Scikit-learn, Tensorflow, Worknotes

Example code for a regression model with multiple layers. In addition to the input of the first layer, it keeps adding new inputs to the later layers. Prepare data import numpy as np import pandas as pd from sklearn.model_selection import train_test_split from sklearn.preprocessing import StandardScaler # create range of monthly dates download_dates = pd.date_range(start=’2019-01-01′, end=’2020-01-01′, ..

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How to optimize hyperparameter of DNN with Keras Tuner and AutoKeras?

     AI, Deep Learning, Keras, Machine Learning, Python, Scikit-learn, Tensorflow, Worknotes

deep ocean scape

Simple example code on hyperparameter optimization for DNN regression models. Prepare data import numpy as np import pandas as pd from sklearn.model_selection import train_test_split from sklearn.preprocessing import StandardScaler # create range of monthly dates download_dates = pd.date_range(start=’2019-01-01′, end=’2020-01-01′, freq=’MS’) # URL from Chrome DevTools Console base_url = (“https://climate.weather.gc.ca/climate_data/bulk_data_e.html?format=csv&” “stationID=51442&Year={}&Month={}&Day=7&timeframe=1&submit=Download+Data”) # add format option to year ..

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How to develope a regression model with Keras?

     AI, Data, Deep Learning, Keras, Machine Learning, Pandas, Python, Scikit-learn, Tensorflow, Worknotes

trees in spring, summer, autumn and winter

Example code for developing a regression model with keras. It can also answer following questions: Prepare data Read data import numpy as np import pandas as pd import matplotlib.pyplot as plt from sklearn.model_selection import train_test_split # create range of monthly dates download_dates = pd.date_range(start=’2019-01-01′, end=’2020-01-01′, freq=’MS’) # URL from Chrome DevTools Console base_url = (“https://climate.weather.gc.ca/climate_data/bulk_data_e.html?format=csv&” ..

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How to apply Scikit-learn transformers to do feature engineering?

     AI, Data Analytics, Deep Learning, Machine Learning, Python, Scikit-learn, Worknotes

Beautiful trees landscape image by AI

Example code for transforming a selected group of variables with Sklearn Transformer Wrapper. It can also answer following questions: Prepare data sample import numpy as np import pandas as pd import matplotlib.pyplot as plt from sklearn.model_selection import train_test_split from sklearn.impute import SimpleImputer from sklearn.preprocessing import StandardScaler from sklearn.preprocessing import OneHotEncoder from sklearn.preprocessing import PolynomialFeatures from ..

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How to transform continuous numerical variables into discrete variables?

     AI, Data, Deep Learning, Machine Learning, Numpy, Pandas, Python, Scikit-learn, Worknotes

Example code to transform continuous numerical variables into discrete variables with different methods. It cab also answer the following questions. Prepare data and load functions Code import numpy as np import pandas as pd import matplotlib.pyplot as plt from sklearn.model_selection import train_test_split from feature_engine.discretisation import EqualFrequencyDiscretiser from feature_engine.discretisation import EqualWidthDiscretiser from feature_engine.discretisation import ArbitraryDiscretiser from ..

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How to create and add new features to the dataframe with feature-engine?

     AI, Data, Deep Learning, Machine Learning, Numpy, Pandas, Python, Scikit-learn, Worknotes

A scenic autumn landscape

Example code for creating and adding new features to a data frame using the feature-engine. It also answer following questions: Math features Code import numpy as np import pandas as pd import matplotlib.pyplot as plt from sklearn.model_selection import train_test_split from feature_engine.creation import MathFeatures from feature_engine.creation import RelativeFeatures from feature_engine.creation import CyclicalFeatures # create range of ..

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How to extract date and time features from datetime variables?

     AI, Data, Data Analytics, Deep Learning, Machine Learning, Python, Scikit-learn, Worknotes

painting a breathtaking aerial view of lakes and mountains

Example code about how to extract several date and time features from datetime variables with feature-engine. It can answer following questions: import numpy as np import pandas as pd import matplotlib.pyplot as plt from sklearn.model_selection import train_test_split from feature_engine import transformation as vt # create range of monthly dates download_dates = pd.date_range(start=’2019-01-01′, end=’2020-01-01′, freq=’MS’) # ..

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How to handle missing data?

     AI, Data, Data Analytics, Deep Learning, Machine Learning, Numpy, Pandas, Python, Scikit-learn

Example python code for handling missing data (ref:Python feature engineering cookbook ). Also answer the following questions: import pandas as pd from sklearn.model_selection import train_test_split from sklearn.impute import SimpleImputer from feature_engine.missing_data_imputers import MeanMedianImputer from feature_engine.imputation import ArbitraryNumberImputer from feature_engine.imputation import EndTailImputer from feature_engine.imputation import CategoricalImputer from feature_engine.imputation import RandomSampleImputer from feature_engine.imputation import AddMissingIndicator from feature_engine.imputation ..

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