Syllabus
Lectures
- W1_L1: IS Introduction
- W1_L2: IS2 Fuzzy Sets: SI2_FuzzySets_2023.pdf
- W2_L1: Fuzzy Relations and Fuzzy Systems: SI3_FuzzyRelations_and_Systems_2023.pdf
- W2_L2: Fuzzy Modeling: SI4_FuzzyModelingAndIdentification_2023.pdf
- W3_L1: NN Review and Adaptive Neuro-Fuzzy Systems (ANFIS): SI5_ReviewlNN_Neuro-fuzzy_2023.pdf
- W3 L2: Knowledge Discovery and Feature Selection: SI6_IntelDataAnalysisFeature Selection_2023.pdf
- W4_L1: Deep Learning: Introduction, Autoencoders: SI7_DeepLearning_Intro_2023.pdf
- Feature extraction Deep Learning Example in Matlab: SI7_Autoencoder_DeepDummyExample.rar
- W4_L2: Deep Learning: Convolution Neural Networks, Application Example: SI8_DeepLearning_CNN_2023.pdf
- ConvNets example in Python with Keras (Tensorflow): SI8_MLPandConvNets_Intro_with_Keras.zip
- W5_L1: Deep Learning: Reinforcement Learning: SI9_DeepLearning_Reinfocement Learning.pdf
- W5_L2: Deep Learning: Sequence Learning: SI10_DeepLearning_TextAndSequences_2023.pdf
- RNN and LSTM example with Time series and Text: DeepLearning_SequenceLearningNotebooks.zip
- W6_L1: Deep Learning: Transformers: SI11_DeepLearning_Transformers_2023.pdf
- Transformers example: chapter11_part03_transformer.ipynb
- W6_L2: ALMMo Fuzzy Systems and Deep Fuzzy: ALMMo Fuzzy Systems and Deep Fuzzy.pdf
- W1_P1: Introduction to GitHub
- W1_P2 and W2_P3: Fuzzy Sets and Fuzzy Relations Exercises
- W2_P4: Fuzzy Systems in Python Using PyFume
- W3_P5: Fuzzy Systems in MATLAB
- W3_P6: Neural Networks Using Scikit-Learn
- W4_P7: ANFIS in Python Using Scikit-Fuzzy
- W4_P8: Tensorflow and ConvNets
- W5_P9: Autoencoders and LSTM networks
- W5_P10: Reinforcement Learning
Class Assignments:
Projects:
- List and Guidelines: SI_Project_list_2023.pdf (Updated)
Grades:
- Project grades: SI_ProjectGrades.pdf
- Final Grades and exam grades: SI_FinalGrades.pdf