Probabilities play a big part in AI and machine learning. After all, AI systems are Probabilistic systems that must learn what to do. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms Bayes’ Theorem, Bayesian Classifier, Naive Bayes, and explain how they relate to AI and why it’s important to know about them.
Continue reading AI Today Podcast: AI Glossary Series – Bayes’ Theorem, Bayesian Classifier, Naive Bayes at AI & Data Today.
AI Today Podcast: AI Glossary Series – Perceptron
AI Today Podcast: AI Glossary Series – Bias, Weight, Activation Function, Convergence, and ReLU
AI Today Podcast: AI Glossary Series – (Artificial) Neural Networks, Node (Neuron), Layer
AI Today Podcast: AI Glossary Series – Feature Reduction, Principal Component Analysis (PCA), and t-SNE
AI Today Podcast: AI Glossary Series – Feature and Feature Engineering
AI Today Podcast: AI Glossary Series – Regression and Linear Regression
AI Today Podcast: AI Glossary Series- Clustering, Cluster Analysis, K-Means, Gaussian Mixture Model
AI Today Podcast: AI Glossary Series – Deep Blue
AI Today Podcast: AI Glossary Series: Symbolic Systems & Expert Systems
AI Today Podcast: AI Glossary Series – Random Forest and Boosted Trees
AI Today Podcast: AI Glossary Series – Ensemble Models
AI Today Podcast: AI Glossary Series – Decision Trees
AI Today Podcast: AI Glossary Series – Support Vector Machine & Kernel Method
AI Today Podcast: AI Glossary Series: K-Nearest Neighbor and Lazy Learning
AI Today Podcast: AI Glossary Series – Classification & Classifier, Binary Classifier, Multiclass Classifier, Decision Boundary
AI Today Podcast: How AI and Project Management Fit Together: Interview with Bill Raymond, Agile in Action Podcast
AI Today Podcast: AI Glossary Series: Overfitting, Underfitting, Bias, Variance, Bias/Variance Tradeoff
AI Today Podcast: AI Glossary Series – Dimension, Curse of Dimensionality, Dimensionality Reduction
AI Today Podcast: AI Glossary Series- Pattern Recognition
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