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Here are the source codes from my Machine Learning course from the lab sessions. If you have the intention to add something to it, please give a pull request.

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README.md
README.md
 
 
W01 - Introduction to Machine Learning.ipynb
W01 - Introduction to Machine Learning.ipynb
 
 
W02 - Data Preprocessing.ipynb
W02 - Data Preprocessing.ipynb
 
 
W03 - Data Representation & Feature Engineering.ipynb
W03 - Data Representation & Feature Engineering.ipynb
 
 
W04 - Regression & Decision Tree Induction.ipynb
W04 - Regression & Decision Tree Induction.ipynb
 
 
W05 - K-Nearest Neighbors.ipynb
W05 - K-Nearest Neighbors.ipynb
 
 
W06 - Naive-Bayes Classifier & Support Vector Machine.ipynb
W06 - Naive-Bayes Classifier & Support Vector Machine.ipynb
 
 
W07 - Deep Learning.ipynb
W07 - Deep Learning.ipynb
 
 
W08 - K-Means Clustering.ipynb
W08 - K-Means Clustering.ipynb
 
 
W08 - K-Medoids Clustering.ipynb
W08 - K-Medoids Clustering.ipynb
 
 
W08 - K-Modes Clustering.ipynb
W08 - K-Modes Clustering.ipynb
 
 
W09 - Hierarchical Clustering.zip
W09 - Hierarchical Clustering.zip
 
 
W10 - DBSCAN Algorithm & Association Rule Learning.ipynb
W10 - DBSCAN Algorithm & Association Rule Learning.ipynb
 
 
W11 - Reinforcement Learning.zip
W11 - Reinforcement Learning.zip
 
 
W12 - Model Selection.ipynb
W12 - Model Selection.ipynb
 
 
w13 - Evaluation Techniques.ipynb
w13 - Evaluation Techniques.ipynb
 
 

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Machine-Learning-Lab-Works

Here are the source codes from my Machine Learning course from the lab sessions. If you have the intention to add something to it, please give a pull request.

Requirements for running these Python scripts :

a. Anaconda

b. Jupyter Notebook, Visual Studio Code, or any Python IDE

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Here are the source codes from my Machine Learning course from the lab sessions. If you have the intention to add something to it, please give a pull request.

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