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university-projects

These are the assignments, projects and lectures that I did during my education as graduate student of Artificial Intelligence at CE@STU

Notebook Concepts Packages Description
preliminaries.ipynb Preliminaries & Numpy Numpy, Scikit-Learn Deep Learning course assignment
batchnorm-and-dropout.ipynb Batch Normalization & Dropout Numpy Deep Learning course assignment
CIFAR10-classification.ipynb Classification using Neural Net PyTorch Deep Learning course assignment
FashionMNIST-CNN.ipynb CNN and Data Augmentation PyTorch Deep Learning course assignment
CIFAR10-ResidualNet.ipynb Residual network architecture PyTorch Deep Learning course assignment
Pedestrian-dataset-instance-segmentation.ipynb Finetuning Mask R-CNN for Instance Segmentation PyTorch Deep Learning course assignment
language-model-{1,2}.ipynb Working with text data and RNNs PyTorch, NLTK Deep Learning course assignment
neural-machine-translation.ipynb Neural Machine Translation using Seq2Seq RNN with Attention PyTorch Deep Learning course assignment
GAN.ipynb Generative Adversarial Networks PyTorch Deep Learning course assignment
VAE.ipynb Variational Autoencoder PyTorch Deep Learning course assignment
RL-actor-critic.ipynb Reinforcement Learning with Actor-Critic algorithm PyTorch, Gym Deep Learning course assignment
Q-learning.ipynb Q-Learning using DNN PyTorch, Gym Deep Learning course assignment
RL-policy-gradient.ipynb Reinforcement Learning with Policy Gradient PyTorch Deep Learning course assignment
COCO-image-captioning-{1,2}.ipynb Image Captioning using VGG, BERT as embedding layer and Attention (in 2) PyTorch, Transformers, NLTK Deep Learning course final project
Clustering.ipynb Clustering Bio data(Gene expression profiles) Scikit-Learn, Scvi, Scanpy, Numpy My lecture in Machine Learning for BioInformatics course as teaching assistant
Ensemble-learning.ipynb Applying Ensemble Learning on Bio data(Obsessive Psychiatric Syndrome Gene expression profiles) Scikit-Learn, Numpy, GEOparse My lecture in Machine Learning for BioInformatics course as teaching assistant
neuron-group-simulation-with-DE.ipynb Simulating Neuron group activity using differential equations brian2 Neuroscience course assignment
hodgkin-huxely-excitatory-inhibitory-simulation.ipynb Simulating Hodgkin-Huxely Excitatory-Inhibitory neural networks brian2, Numpy Neuroscience course assignment
excitatory-and-inhibitory-neuron-groups.ipynb Simulating Excitatory and Inhibitory neuron groups activity brian2, Numpy Neuroscience course assignment

Deep Learning course was instructed in spring 2020 by Dr. Soleymani at CE@STU. Neuroscience course was instructed in Fall 2020 by Dr. Karbalai Aghajan at EE@STU. Finally Machine Learning for BioInformatics course was instructed in spring 2021 by Dr. Soleymani and Dr. Sharifi Zarchi at CE@STU.