Delete a folder in Google Colab
To delete a folder in Google Colab, you need to first remove all the files and subfolders within it. Here is a step-by-step guide on how to do this using Python and shell commands:
Category: Python
Quantile-based discretization of continuous variables
n Pandas library in Python pd.qcut is a function for performing quantile-based discretization of continuous variables. Quantile-based discretization involves dividing a continuous variable into discrete intervals or bins based on the distribution of its values. This process ensures that each bin contains approximately the same number of observations, making it useful for creating categories or…
Get available Hyperparameters
get_params() is a method provided by scikit-learn estimators (such as classifiers, regressors, transformers, etc.) that returns a dictionary of the estimator’s parameters. These parameters are the hyperparameters that define the behavior of the estimator and can be tuned during the model selection or hyperparameter optimization process. Here’s a simple example of how you might use…
Handling missing values with SimpleImputer
SimpleImputer is a class in scikit-learn, a popular machine learning library in Python, used for handling missing values in datasets. It provides a simple strategy for imputing missing values, such as filling missing entries with the mean, median, most frequent value, or a constant. Here’s a basic example of how you might use SimpleImputer: This…
Parameter stratify from method train_test_split in scikit Learn
In the context of the train_test_split function in machine learning, the stratify parameter is used to ensure that the splitting process preserves the proportion of classes in the target variable. When you set stratify=y, where y is your target variable, the data is split in a way that maintains the distribution of classes in both…
CDF plot of Numerical columns
The provided code below generates a grid of subplots (dynamic rows and 2 columns) and plots cumulative distribution function (CDF) plots for numerical variables in a DataFrame (df).
Standardizing features by StandardScaler
n scikit-learn (sklearn), the StandardScaler is a preprocessing technique used to standardize features by removing the mean and scaling them to have a unit variance. Standardization is a common step in many machine learning algorithms, especially those that involve distance-based calculations or optimization processes, as it helps ensure that all features contribute equally to the…
NumPy function argmax
np.argmax is a NumPy function that returns the indices of the maximum values along a specified axis in an array. If the input array is multi-dimensional, you can specify the axis along which the maximum values are computed. Here’s a simple example: Output: In this example, np.argmax(arr) returns the index (position) of the maximum value…
NumPy function argsort
np.argsort is a NumPy function that returns the indices that would sort an array along a specified axis. It performs an indirect sort on the input array and returns an array of indices that represent the sorted order of the elements. The returned indices can be used to construct a sorted version of the input…
Import your functions library to a Google Colab notebook
To import a function from a separate Jupyter Notebook (.ipynb file) into another notebook, you can use the %run magic command: