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Top 10 Machine Learning Algorithms Every Programmer Should Know #1. Linear Regression: The Oldie but Goodie #2. Logistic Regression: It’s Not All About Numbers #3. Decision Trees: Make Decisions Like a Machine #4. Naive Bayes: A Sincere Approach to Classifying #5. K-Nearest Neighbors (K-NN): Birds of the Same Feather #6. Support Vector Machines (SVM): Playing the Field #7. K-Means Clustering: Finding Your Tribe #8. Random Forest: More Trees, Please! #9. Neural Networks: Mimicking the Human Brain #10. Gradient Boosting & AdaBoost: Boosting Your Method to Success Wrapping Up Our Wild Ride Through the World of Machine Learning Level Up Coding
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June 6, 2023
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Artificial Intelligence
Naive Bayes Classification Background: Bayes’ Theorem The Naive Bayes Model Bernoulli Naive Bayes Categorical Naive Bayes Multinomial Naive Bayes Laplace Smoothing Gaussian Naive Bayes Naive Bayes Classifiers in Scikit-Learn Document Classification Example Summary Final Notes
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June 5, 2023
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Artificial Intelligence
Conditional Probablity & Bayes’ Theorem for Data Science Table of Contents Conditional Probability The law of total probability Bayes’ Theorem When to use Conditional Probability & when to use Bayes’ Theorem? Let’s think higher together!
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April 27, 2023
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