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S8_Artificial Intelligence
S8_Artificial Intelligence
75 Students enrolled
Created by: Konstantinos Liagkouras
Last Updated: 23rd February 2024
English
Requirements
S8_Artificial Intelligence
Description
S8_Artificial Intelligence
Content
Introduction
Introduction to Artificial intelligence
Introduction to Python programming
Introduction to Numerical Python
Supervised Learning
Introduction to Regression Analysis
Introduction to Logistic Regression
Regression Analysis Exercises
Introduction to K-Nearest Neighbors
Introduction to Random Forest
Exercises in Random Forest
Introduction to Naive Bayes
Exercises in Naive Bayes
Introduction to Support vector machine (SVM)
Exercises in SVM
Solving Regression and Classification problems with SVM
Introduction to Time Series
Exercises in Time Series
Sentiment Analysis
Text Mining with Python
Introduction to Sentiment Analysis
Pre-Trained Sentiment Analyzers
Speech Recognition System with Python
Artificial Neural Networks (ANN)
Introduction to Artificial Neural Networks
Introduction to Recurrent Neural Network
Introduction to Convolutional Neural Networks
Reinforcement Learning
Introduction to Reinforcement Learning
Exercises in Q Learning
Networks in Python
Unsupervised Learning
Introduction to Unsupervised Learning
Hierarchical Clustering
Optimization
Introduction to Fuzzy Systems
Implementation of Genetic Algorithms in Python
Introduction to Multiobjective Optimization
Multi-objective Evolutionary Algorithms with Python
Critical Path Method (CPM)
Introduction to Linear Programming
Exercises in Linear Programming
Introduction to Brownian Motion
Hill Climbing in Python
Expert Systems
Introduction to Expert Sytems
Exercises in Expert Systems
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Konstantinos Liagkouras
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