machine-learning-lab

Machine Learning Lab

Topics

• Lab1: Logistic Regression
• Lab2: Support Vector Machine (SVM)
• Lab3: Decision Tree and Random Forest
• Lab4: K-Nearest Neighbour (KNN)
• Lab5: Evaluation Metrics
• Lab6: Sentiment Analysis
• Lab7: Linear Regression
• Lab8: KMeans

Lab 01: Logistic Regression

• https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegression.html
• https://towardsdatascience.com/logistic-regression-using-python-sklearn-numpy-mnist-handwriting-recognition-matplotlib-a6b31e2b166a
• https://www.datacamp.com/tutorial/understanding-logistic-regression-python

Lab 02: Support Vector Machine

• https://www.tutorialspoint.com/scikit_learn/scikit_learn_support_vector_machines.htm

Lab3: Decision Tree and Random Forest

• https://www.tutorialspoint.com/scikit_learn/scikit_learn_decision_trees.htm
• https://scikit-learn.org/stable/modules/generated/sklearn.ensemble.RandomForestClassifier.html

Lab 05: Evaluation Metrics Used in Machine Learning

• Dataset: https://www.kaggle.com/datasets/fedesoriano/heart-failure-prediction
• Tutorial: https://www.kaggle.com/code/pythonafroz/evaluation-metrics-used-in-machine-learning

Lab 06: Sentiment Analysis

• Dataset: IMDB Dataset of 50K Movie Reviews
• Tutorial: https://www.kaggle.com/code/lakshmi25npathi/sentiment-analysis-of-imdb-movie-reviews

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Machine Learning Resources

• https://github.com/rasbt/python-machine-learning-book-3rd-edition
• https://cs229.stanford.edu/
• CS229 Final Project Spring 2023 public
• https://www.youtube.com/watch?v=OgK8JFjkSto&list=PLTKMiZHVd_2KyGirGEvKlniaWeLOHhUF3&ab_channel=SebastianRaschka Sebastian Raschka ML playlist