How can you showcase your sklearn skills in your portfolio?

Repository files navigation ... scikit-learn is a Python module for machine learning built on top of SciPy and is distributed under the 3-Clause BSD license. The ... Applications: Spam detection, image recognition. Algorithms: Gradient boosting, nearest neighbors, random forest, logistic regression, and more ... sklearn.linear_model import Perceptron from sklearn.model_selection import train_test_split from sklearn.metrics import accuracy_score. Part 1. Exploratory ... from sklearn.metrics import roc_curve, roc_auc_score probabilities = classifier.predict_proba(X_test) fpr, tpr, _ = roc_curve(y_test, probabilities[:, 0]) ... Jul 28, 2021 ... Yes, scikit-learn can use for production, or any small python object like scikit-learn can use for production. For API, just scale up ... Sep 11, 2018 ... The SubsetRandomSampler samples randomly from a list of indices. As it won't create these indices internally, you might want to use something ... Aug 17, 2023 ... Top 10 use cases of scikit-learn: · Classification · Regression · Clustering · Dimensionality Reduction · Feature Selection · Model Selection ... Overview . In addition to the native interface, XGBoost features a sklearn estimator interface that conforms to sklearn estimator guideline. It supports ... Aug 14, 2022 ... This algorithm is used to predict categorical variables using independent variables which are continuous. It identifies which of the target ... Aug 13, 2024 ... Scikit Learn is a robust library available in Python that provides a selection of tools for machine learning and statistical modeling.