Lecuture Notes for Topics in Machine Learning

  • 10/10 Introduction
    • 　　　 - empty_R.ipynb
    　　　 - 01LinearRegression.R.ipynb
    　　　 - A note to run cells in R notebooks

  • 10/17 No class

  • 10/24 No class

  • 10/31 Nearest Neighbor and Related Topics
    • 　　　 - 02NearestNeighborBasicAlgorithm_R.ipynb

  • 11/07 Decision Tree and Overfitting (tentative, to be shortened)
    • 　　　 - 03DecisionTree_R.ipynb

  • 11/14 No class

  • 11/21 Bayesian Inference and naive Bayes (tentative, to be shortened) (Class room is General Research Building, S9-1, Room E205)

  • 11/21 Naive Bayes (updated 2019/11/26 24:00)
    • 　　　 - 04NaiveBayes_playtennis_R.ipynb (2019/11/26 24:00)
    　　　 - TwentyNewsGroups_R.ipynb (2019/11/27 23:00)

  • 11/28 Modelselection, AIC, and MDL (updated 2019/11/27 23:00)

  • 12/05 Linear SVM (2019/11/27 24:00)
    • 　　　 - Training/Validation/Test dataset (2019/12/03 23:00)

  • 12/12 Non-Linear SVM and SVR (2019/12/03 23:00)
    • 　　　 - Random Forest (2019/12/08 22:00)
    　　　 - Laplace correction (2019/12/08 22:00)

  • 12/19 Neural Networks: an Introduction (2019/12/17 15:30)
    • 　　　 - Neural Networks exercise notebook: iris (2019/12/17 18:00)
    　　　 - Neural Networks exercise notebook: banknote (2019/12/17 18:00)

  • 01/09 MLP and related topics (2020/01/08 22:10)
    • 　　　 - 2.1-a-first-look-at-a-neural-network.R (2020/01/08 17:20)
    　　　 - 2.1-a-first-look-at-a-neural-network (2020/01/08 17:20)

  • 01/16 ML, NLP, and others (2020/01/15 21:30)
    • 　　　 - 3.4-classifying-movie-reviews.R (2020/01/08 17:20)
    　　　 - 3.5-classifying-movie-reviews (2020/01/08 17:20)

  • 01/23 Homework (2020/01/20 23:50)
    • 　　　 - 5.1-introduction-to-convnets.R (2020/01/20 23:50)
    　　　 - 5.2-using-convnets-with-small-datasets.R (2020/01/20 23:50)
    　　　 - 5.3-using-a-pretrained-convnet.R (2020/01/20 23:50)
    　　　 - 5.3-using-a-pretrained-convnet-svm.R (2020/01/23 08:00)
    　　　 - 5.3-using-a-pretrained-convnet-MobileNet.R (2020/01/20 23:50)
    　　　 - 5.1-introduction-to-convnets (2020/01/20 23:50)
    　　　 - 5.2-using-convnets-with-small-datasets (2020/01/20 23:50)
    　　　 - 5.3-using-a-pretrained-convnet (2020/01/20 23:50)
    　　　 - 5.3-using-a-pretrained-convnet-MobileNet (2020/01/20 23:50)

  • 01/23, 30 (the last class) Some notes (2020/01/22 20:00, 2020/01/30 12:30)
    • 　　　 - 3.5-classifying-newswires.R (2020/01/08 17:20)
    　　　 - 3.6-predicting-house-prices.R (2020/01/15 21:30)
    　　　 - 4.4-overfitting-and-underfitting.R (2020/01/15 21:30)
    　　　 - 3.6-classifying-newswires (2020/01/08 17:20)
    　　　 - 3.7-predicting-house-prices (2020/01/15 21:30)
    　　　 - 4.4-overfitting-and-underfitting (2020/01/15 21:30)

    　　　 - 5.4-visualizing-what-convnets-learn.R (2020/01/30 12:30)
    　　　 - 5.4-visualizing-what-convnets-learn (2020/01/30 12:30)

  • **/** Introduction to Deep Neural Networks
    • 　　　 - R notebooks (in "Deep Learning with R") modified to run in Google Colab environment

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