دکتر احمد کلهر - دانشگاه تهران👇🏻
( مقدمه‌ای بر شبکه های عصبی و یادگیری عمیق )
#یادگیری_عمیق

1. Introduction
Natural Neural Networks
Artificial NNs and Applications
Architectures, Activation Functions and Learning in ANNs
Mcculloch & Pitz Neuron
2. Fully Connected Neural Networks
Linear Perceptron, AdaLine and MadaLine
Multi-Layer Perceptron (MLP)
Auto-encoders and Restricted Boltzmann Machine
Deep belief networks
3. Convolutional Neural Networks (CNNs)
Convolutional Neural Networks (CNNs)
Developments and Techniques in CNNs
Some popular Architectures (AlexNet, VGG, ResNet, Inception, MobileNet, DenseNet, and EfficientNet)
4. Region based CNNs
CNNs for Object Detection (RCNN, Mask RCNN, YOLO,...)
CNNs for Object Segmentation (UNet, Mask RCNN, ...)

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5. Recurrent Neural Networks
Recurrent Neural Network(RNN)
Long Short Term Memory (LSTM)
Gated Recurrent Units(GRU)
Some Extensions
6. Transformers
Attention Mechanisms
Vanilla Transformer
Vision Based Transformers
7. Deep Generative Models
Variational Auto-encoders
Generative Adversarial Networks
Flow-based Deep Generative Models
Diffusion Models

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🆔 @ComputerReference

اسلایدهای فصل اول

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جلسه اول.‌فصل اول. #بهار_۱۴۰۲

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جلسه دوم. فصل اول. #بهار_۱۴۰۲

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جلسه سوم. فصل اول. #بهار_۱۴۰۲

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اسلایدهای فصل دوم

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جلسه چهارم. فصل دوم. #بهار_۱۴۰۲

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🆔 @ComputerReference