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This repository contains my notes, assignments, and projects from the Deep Learning Specialization by Andrew Ng, offered on Coursera. The course series provides a comprehensive introduction to deep learning, covering foundational concepts, algorithms, and practical applications in neural networks.

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Deep-Learning

This repository contains my notes, assignments, and projects from the Deep Learning Specialization by Andrew Ng, offered on Coursera. The course series provides a comprehensive introduction to deep learning, covering foundational concepts, algorithms, and practical applications in neural networks. The specialization includes the following:

  1. Neural Networks and Deep Learning: Introduction to deep learning, neural networks, and backpropagation.

  2. Improving Deep Neural Networks: Techniques for training deep networks, including regularization and optimization methods.

  3. Structuring Machine Learning Projects: Best practices for organizing machine learning projects and improving their performance.

  4. Convolutional Neural Networks: Understanding convolutional layers and their use in image recognition tasks.

  5. Sequence Models: Introduction to recurrent neural networks (RNNs) and applications in natural language processing.

The course is ideal for those looking to gain a strong understanding of deep learning principles and how to implement and fine-tune deep learning models using popular frameworks like TensorFlow.

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This repository contains my notes, assignments, and projects from the Deep Learning Specialization by Andrew Ng, offered on Coursera. The course series provides a comprehensive introduction to deep learning, covering foundational concepts, algorithms, and practical applications in neural networks.

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