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Lab -4.2 Agglomerative clustering.ipynb
Lab -4.2 Agglomerative clustering.ipynb
 
 
Lab-2.1 Reg-Simple-Linear-Regression.ipynb
Lab-2.1 Reg-Simple-Linear-Regression.ipynb
 
 
Lab-2.2 Multiple Linear Regression.ipynb
Lab-2.2 Multiple Linear Regression.ipynb
 
 
Lab-2.3 Polynomial Regression.ipynb
Lab-2.3 Polynomial Regression.ipynb
 
 
Lab-2.4 Non-linear Regression.ipynb
Lab-2.4 Non-linear Regression.ipynb
 
 
Lab-3.1 KNN.ipynb
Lab-3.1 KNN.ipynb
 
 
Lab-3.2 Decision Trees.ipynb
Lab-3.2 Decision Trees.ipynb
 
 
Lab-3.3 Logistic Regression.ipynb
Lab-3.3 Logistic Regression.ipynb
 
 
Lab-3.4 SVM (Support Vector Machines).ipynb
Lab-3.4 SVM (Support Vector Machines).ipynb
 
 
Lab-4.1 k-Means.ipynb
Lab-4.1 k-Means.ipynb
 
 
Lab-4.3 DBSCAN Clustering.ipynb
Lab-4.3 DBSCAN Clustering.ipynb
 
 
Lab-5.1 Content-based Recommendation Systems.ipynb
Lab-5.1 Content-based Recommendation Systems.ipynb
 
 
Lab-5.2 Collaborative Filtering on Movies.ipynb
Lab-5.2 Collaborative Filtering on Movies.ipynb
 
 
ML_Final_Project.ipynb
ML_Final_Project.ipynb
 
 
README.md
README.md
 
 

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IBM-DS-8-Machine-Learning-with-Python

Basics of machine learning using an approachable, and well-known programming language, Python.A general overview of Machine Learning topics such as supervised vs unsupervised learning, model evaluation, and Machine Learning algorithms.

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Basics of machine learning using an approachable, and well-known programming language, Python.A general overview of Machine Learning topics such as supervised vs unsupervised learning, model evaluation, and Machine Learning algorithms.

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