| 11-October-2021 |
1.5 hours |
● Class introduction ● Class overview: Class organization, topics overview, software etc. |
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1.5 hours |
● Introduction: what is ML; Problems, data, and tools; Python (I) |
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| 18-October-2021 |
1.5 hours |
● Machine Learning Fundamentals |
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1.5 hours |
● Examples/Applications |
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| 25-October-2021 |
1.5 hours |
● Linear regression; Logistic regression, Neural Networks |
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1.5 hours |
● gradient descent; features ● Overfitting and complexity; training, validation, test data |
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| 1-November-2021 |
1.5 hours |
Introduction to Neural Networks (model of a biological neuron, activation functions, neural net architecture, Perceptron) |
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1.5 hours |
Building Neural Networks (data preprocessing, loss functions, weight initialization, regularization, dropout, batch normalization, Linear classification, Soft max) and Regularization, Gradient Descent & Stochastic Gradient Descent (SGD), Back propagation |
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| 8-November-2021 |
1.5 hours |
Classification problems; decision trees, |
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1.5 hours |
nearest neighbor methods |
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| 15-November-2021 |
1.5 hours |
Linear classifiers, Bayes' Rule |
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1.5 hours |
Naive Bayes Model |
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| 22-November-2021 |
1.5 hours |
Unsupervised learning: clustering |
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1.5 hours |
k-means Clustering Latent space methods; PCA |
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| 29-November-2021 |
1 Hour |
Mid Term |
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| 6-December-2021 |
1.5 hours |
Support vector machines and large-margin classifiers Time series; |
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1.5 hours |
Markov models; |
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| 13-December-2021 |
1.5 hours |
Midterms` |
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1.5 hours |
Introduction to Convolutional Neural Networks (CNN) and its components (Convolution and Pooling Layers), |
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| 20-December-2021 |
1.5 hours |
Convolutional Neural Network case studies (Imagenet/ AlexNet/ Minist/Iris), |
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1.5 hours |
Introduction to Natural Language Processing (NLP) |
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| 27-December-2021 |
1.5 hours |
Learning word and sentences embedding |
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1.5 hours |
Introduction to Natural Language Processing (NLP) |
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| 3-January-2022 |
1.5 hours |
Learning word and sentences embedding (Continued) |
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1.5 hours |
Case Study (Deep Learning based Chatbot) |
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| 10-January-2022 |
1.5 hours |
Introduction to recurrent networks (RNNs, LSTMS, etc.) |
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1.5 hours |
Applications of Recurrent neural networks to different NLP tasks |
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| 17-January-2022 |
1.5 hours |
Autoencoders |
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1.5 hours |
Autoencoders |
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| 24-January-2022 |
1.5 hours |
GANs |
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1.5 hours |
GANs |
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| 31-January-2022 |
2 Hour |
Final Term |
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