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Latest updates on design, engineering, and digital identity.
![[3 - 2 FNN/ANFIS] Implanting 'Intuition' into Neural Networks: The Learning Fuzzy System](https://pub-f9bcb810fe534d209cb2503151c026eb.r2.dev/journal/1779003433666-ljvnnt.png)
Neural Network. From Basic to Hybrid
[3 - 2 FNN/ANFIS] Implanting 'Intuition' into Neural Networks: The Learning Fuzzy System
Explore the fusion of Fuzzy Logic (F) and Neural Networks (T) through FNN and ANFIS. Learn about the 5-layer architecture, high-speed hybrid learning
![[2 - 3 Fuzzy Logic] AI That Understands "Appropriately": Membership Functions and Linguistic Variables](https://pub-f9bcb810fe534d209cb2503151c026eb.r2.dev/journal/1778824880509-i8ijix.png)
Neural Network. From Basic to Hybrid
[2 - 3 Fuzzy Logic] AI That Understands "Appropriately": Membership Functions and Linguistic Variables
Explore Fuzzy Logic: How machines use membership functions and linguistic variables to mimic human intuition between 0 and 1.
![[2 - 3 RBFNN] When Speed is Life: Boundary-Based Ultra-Fast Neural Networks](https://pub-f9bcb810fe534d209cb2503151c026eb.r2.dev/journal/1778654208742-b9exib.png)
Neural Network. From Basic to Hybrid
[2 - 3 RBFNN] When Speed is Life: Boundary-Based Ultra-Fast Neural Networks
Explore RBFNN's local response philosophy and ultra-fast computation. Learn how RBF networks optimize real-time control and engineering.
![[2 - 2 RNN/LSTM] Yesterday’s Data Creates Today’s Answer: Time-Series Data and Memory](https://pub-f9bcb810fe534d209cb2503151c026eb.r2.dev/journal/1778569855702-o2w8to.png)
Neural Network. From Basic to Hybrid
[2 - 2 RNN/LSTM] Yesterday’s Data Creates Today’s Answer: Time-Series Data and Memory
How does AI understand time and context? Deep dive into Recurrent Neural Networks (RNN) and Long Short-Term Memory (LSTM) with PyTorch examples. Learn
![[2 - 1 CNN] How AI Sees the World: Image Filters and Feature Extraction](https://pub-f9bcb810fe534d209cb2503151c026eb.r2.dev/journal/1778479570731-qcm385.png)
Neural Network. From Basic to Hybrid
[2 - 1 CNN] How AI Sees the World: Image Filters and Feature Extraction
Why CNNs outperform MLPs in vision tasks. Explore the mechanics of filters and feature extraction through interactive simulations and PyTorch examples
![[1 - 4 Optimization] Breaking the Barriers of Depth](https://pub-f9bcb810fe534d209cb2503151c026eb.r2.dev/journal/1778220060328-fijolk.png)
Neural Network. From Basic to Hybrid
[1 - 4 Optimization] Breaking the Barriers of Depth
Master Deep Learning Optimization: From ReLU to Batch Normalization. Learn how to overcome Vanishing Gradients and Overfitting with advanced technique
![[1 - 3 MLP] Why 'Deep' Learning? Solving Complex Problems Through Layer Stacking](https://pub-f9bcb810fe534d209cb2503151c026eb.r2.dev/journal/1778134983775-1g7okp.png)
Neural Network. From Basic to Hybrid
[1 - 3 MLP] Why 'Deep' Learning? Solving Complex Problems Through Layer Stacking
Explore MLP & Universal Approximation Theorem. Learn why depth matters, activation roles, and Vanishing Gradients.
![[1 - 2 Beyond the Perceptron]: Solving Complexity with MLP and Backpropagation](https://pub-f9bcb810fe534d209cb2503151c026eb.r2.dev/journal/1777963108258-arpj61.png)
Neural Network. From Basic to Hybrid
[1 - 2 Beyond the Perceptron]: Solving Complexity with MLP and Backpropagation
Unlock the heart of AI. Discover how Backpropagation and the Chain Rule train neural networks to solve complex problems through mathematical precision
![[1 - 1 Perceptron] The First Step Toward AI.](https://pub-f9bcb810fe534d209cb2503151c026eb.r2.dev/journal/1777707081708-510141.png)
Neural Network. From Basic to Hybrid
[1 - 1 Perceptron] The First Step Toward AI.
Mastering the Perceptron: The First Step Toward AI. Explore the core of neural networks, the XOR problem, and the road to deep learning in this guide.