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Machine Learning Group 1
Machine Learning Group 1
135 Students enrolled
Created by: Konstantinos Liagkouras
Last Updated: 23rd September 2022
English
Requirements
Machine Learning Group 1Machine Learning
Description
Machine Learning Group 1
Content
Introduction to Machine learning
Introduction to Machine Learning and Setting up the Programming Environment
Supervised Machine Learning
Introduction to Linear Regression
Ordinary Least Squares Regression
Introduction to Logistic Regression
Multiple Logistic Regression
How to use P value for Regression Analysis
Introduction to K-Nearest Neighbors (KNN)
K-Nearest Neighbors (KNN) for Classification and Regression
Introduction to Support vector machine (SVM)
Support Vector Regression in Python
Exercises in Support Vector Machine
Fine tuning of SVM algorithm
Introduction to Time Series
Fine Tuning of ARIMA model
Introduction to Naive Bayes
Exercises in Naive Bayes
Text Classification by using Naive Bayes
Text Mining in Python
Sentiment Analysis in Python
Exercises in Sentiment Analysis with Python
Sentiment Analysis with TextBlob
Web Scraping With Python
Introduction to Random Forest
Implementation of Decision Trees by using Sklearn
Solving Regression and Classification problems with Random Forest - Python
Introduction in Artificial Neural Networks (ANN)
Exercise in Artificial Neural Networks ANN
Exercises in ANNs
Introduction to Genetic Algorithms
Predict Sentiment from Movie Reviews by using Artificial Neural Networks
Exercises in Genetic Algorithms
Recommender system with Python
Introduction to Fuzzy Logic
Brownian Motion
Image Processing with Python
Image Classification with ANN
Convolutional Neural Networks for Image Classification
Recurrent Neural Networks
Applications in Python of RNN
Applications of ANN in Python
Solving Classification Problems with different Machine Learning techniques
Solving Regression Problems with different machine learning techniques
How to improve the classification results
Unsupervised Learning
Introduction to Unsupervised Learning
K-Mean Clustering
Principal Component Analysis
Exercises in Unsupervised Learning
Dimensionality Reduction and Data Visualization PCA
Optimization Techniques
Linear Programming
Mixed Integer Linear programming
Networks in Python
Reinforcement Learning
Introduction to Reinforcement Learning
Q-Learning with Python
Q - Learning with Python
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