Participants will gain a strong understanding of the fundamental concepts behind CNNs, including convolutional layers, pooling, and activation functions.
Participants will learn various techniques for training CNNs, including backpropagation, optimization algorithms, and weight initialization.
Participants will become proficient in testing and evaluating CNN models using metrics like accuracy, precision, recall, F1 score, and ROC-AUC.
Understanding CNN Fundamentals: The fundamental concepts behind CNNs, including convolutional layers, pooling, and activation functions.
Training Techniques: Learn various techniques for training CNNs, including backpropagation, optimization algorithms, and weight initialization.
Testing and Evaluation:The proficient in testing and evaluating CNN models using metrics like accuracy, precision, recall, F1 score, and ROC-AUC.
Hyperparameter Tuning: Understanding how to effectively tune hyperparameters, such as learning rates, batch sizes, and model architecture, to optimize CNN performance.
Data Preprocessing: Learning about data preprocessing techniques like normalization, augmentation, and handling imbalanced datasets to improve CNN performance.
Transfer Learning: Understanding how to leverage pre-trained CNN models for specific tasks and fine-tune them.
Handling Overfitting: Techniques for preventing overfitting in CNNs, such as dropout, regularization, and early stopping.
Advanced Architectures: Exploring more advanced CNN architectures like VGG, ResNet, and Inception and understanding their advantages and use cases.
Practical Implementation: Hands-on experience with implementing CNNs using popular deep learning frameworks like TensorFlow or PyTorch.
Real-world Applications: Demonstrating how CNNs are applied in various domains, such as computer vision, natural language processing, and healthcare.
Research Trends: Keeping participants informed about the latest research trends and developments in the field of CNNs.
Case Studies: Analyzing real-world case studies and projects that highlight the practical use of CNNs in solving specific problems.
21st Century Engineering College in Coimbatore
World is transforming everyday. In the rapidly evolving engineering landscape, we have an Increased responsibility to transform the engineering education from traditional curriculum to meet the 21st century skills like Creativity, Critical Thinking, Collaboration and Communication. Through our unique and strategic approach we enable our students to learn beyond and prepare them for life long success.
