Technical Expertise:

• Artificial Neural Networks: Utilizing Multilayer Perceptrons (MLPs), Recurrent Neural Networks (RNNs), and Self-Organizing Maps (SOMs) for complex pattern recognition.
• Neuro-Fuzzy Adaptive Networks: Implementing Adaptive Network-Based Fuzzy Inference Systems (ANFIS) and Supervised Fuzzy Neural Inference Systems (SuPFuNIS) for robust adaptive learning.
• Other Classification Methods: Employing k-Nearest Neighbors (k-NN), Decision Trees, and Support Vector Machines (SVMs) for diverse classification tasks.
• Clustering Techniques: Applying k-Means, Hierarchical Clustering, and DBSCAN for insightful data segmentation.
• Natural Language Processing (NLP): Leveraging BERT, GPT, and LSTM networks for advanced text analysis and understanding.
• Computer Vision: Utilizing Convolutional Neural Networks (CNNs) and OpenCV for image and video analysis.
• Reinforcement Learning: Implementing Q-Learning, Deep Q-Networks (DQN), and Policy Gradient Methods for decision-making models.