top machine learning algorithms

1. Top Machine Learning Algorithms https://1stepgrow.com/course/advance-data-science-and-artificial-intelligence-course/

2. Table Of Content 1. Linear regression 2. Logistic regression 3. Decision tree 4. SVM algorithm 5. Naive Bayes algorithm https://1stepgrow.com/course/advance-data-science-and-artificial-intelligence-course/

3. Linear regression A machine learning algorithm based on supervised learning is linear regression. It executes a regression operation. Regression uses independent variables to model a goal-accurate prediction. It is primarily used to determine how variables and predictions relate to one another. https://1stepgrow.com/course/advance-data-science-and-artificial-intelligence-course/

4. Logistic regression One of the more often used Machine Learning algorithms within the category of Supervised Learning is logistic regression. A predetermined set of independent factors predicts the categorical dependent variable. https://1stepgrow.com/course/advance-data-science-and-artificial-intelligence-course/

5. Decision tree The decision tree is the most effective and well-liked technique for categorization and predictions. A decision tree is a type of tree structure that resembles a flowchart, where each internal node represents a test on an attribute, each branch a test result, and each leaf node (terminal node) a class label. https://1stepgrow.com/course/advance-data-science-and-artificial-intelligence-course/

6. SVM algorithm A supervised machine learning approach called Support Vector Machine (SVM) is used for regression and classification. Although we also refer to regression concerns, categorization is the most appropriate term. Finding a hyperplane in an N-dimensional space that separates the data points is the goal of the SVM algorithm. https://1stepgrow.com/course/advance-data-science-and-artificial-intelligence-course/

7. Naive Bayes algorithm Naive Bayes is a Machine learning algorithm used to analyze vast amounts of data; it is the suggested strategy even when working with data that has millions of data records. It produces excellent results for natural language processing applications like sentimental analysis. https://1stepgrow.com/course/advance-data-science-and-artificial-intelligence-course/

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