Logistic regression
Predicts binary classes
Any time
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- scikit-learn - WikipediaMachine learning libraryscikit-learn is a free and open-source machine learning library for the Python programming language. It features various classification, regression and clustering algorithms including support-vector machines, random forests, gradient boosting, k-means and DBSCAN, and is ...See more on Wikipedia
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Machine learning is a subfield of artificial intelligence that enables computers to learn from data and make predictions or decisions without being explicitly programmed. Python is a popular language for machine learning due to its simplicity and the availability of powerful libraries like Scikit-learn, TensorFlow, and Keras.
Key Machine Learning Algorithms
1. Linear Regression
Linear Regression is used for predicting a continuous-valued attribute. It models the relationship between a dependent variable and one or more independent variables by fitting a linear equation to the observed data.
from sklearn.linear_model import LinearRegressionimport numpy as np# Sample dataX = np.array([[1], [2], [3], [4], [5]])y = np.array([1, 3, 2, 3, 5])# Create and fit the modelmodel = LinearRegression()model.fit(X, y)# Make predictionspredictions = model.predict(X)print(predictions)Copied!âś•Copy2. Logistic Regression
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Learn about various Machine Learning Algorithms like Linear regression, logistic regression, Naive Bayes, decision trees etc.
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- Courserahttps://www.coursera.org › specializations › machinelearning
Machine Learning with Python | Machine Learning for Beginners
Sponsored Learn the essential machine learning concepts from DeepLearning.AI and Stanford Online. Get started with machine learning with basic math and programming knowledge.
Deep dive into Machine Learning Algorithms Python