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S9_Artificial Intelligence
S8_Artificial Intelligence
47 Students enrolled
Created by: Konstantinos Liagkouras
Last Updated: 16th September 2024
English
Requirements
S8_Artificial Intelligence
Description
S8_Artificial Intelligence
Content
Introduction
Introduction to AI and Entrance Test
Introduction to Python Programming
Introduction to Python
Visualization with Matplotlib
Regression Analysis with Python
Introduction to Regression Analysis with Python
Logistic Regression in Python
Introduction to Time Series with python
Time Series Analysis with python
Time Series Forecasting with python
Supervised Learning Techniques
Introduction to K-Nearest Neighbors with Python
Dataset Visualization techniques
Introduction to Random Forest
Introduction to Support vector machine with python
Exercises in Support vector machine with python
Support vector Regression with python
Introduction to Naive Bayes
Naive bayes for Text Classification
Introduction to Artificial Neural Networks
Convolutional neural networks with python
Exercises in Artificial Neural Networks (python)
Artificial Neural Networks for solving real problems with python
Reinforcement Learning Techniques
Introduction to Reinforcement Learning
Exercises in Reinforcement Learning with python
Unsupervised Learning Techniques
Introduction to Unsupervised Learning
Hierarchical Clustering with python
Exercises in unsupervised learning with python
Artificial Neural Networks with Python
Sentiment Analysis
Text Mining with Python
Sentiment Analysis with python
Pre-trained Sentiment Analyzers with python
Optimization
Linear Programming with Python
Genetic Algorithms with python
Introduction to Fuzzy Logic
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Konstantinos Liagkouras
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