Certificate in Deep Learning Model Development
-- ViewingNowThe Certificate in Deep Learning Model Development is a comprehensive course designed to equip learners with essential skills in deep learning model development. This course emphasizes the importance of deep learning, a subset of machine learning, which has revolutionized industries by providing powerful predictive capabilities.
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⢠Fundamentals of Deep Learning: Introduction to deep learning, neural networks, backpropagation, and gradient descent.
⢠Convolutional Neural Networks (CNNs): Understanding of CNN architecture, design principles, and practical applications.
⢠Recurrent Neural Networks (RNNs): Learning about RNN architecture, long short-term memory (LSTM), and gated recurrent units (GRU).
⢠Deep Learning Frameworks: Hands-on exposure to popular deep learning frameworks, such as TensorFlow, Keras, and PyTorch.
⢠Natural Language Processing (NLP): Exploration of text vectorization, word embeddings, and NLP applications with deep learning.
⢠Computer Vision: Image recognition, object detection, and segmentation using deep learning models.
⢠Generative Models: Introduction to generative models, such as Variational Autoencoders (VAEs) and Generative Adversarial Networks (GANs).
⢠Transfer Learning and Fine-tuning: Techniques for leveraging pre-trained models, transfer learning, and fine-tuning for computer vision and NLP tasks.
⢠Evaluation Metrics and Hyperparameter Tuning: Understanding of evaluation metrics and strategies for hyperparameter tuning.
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