https://github.com/nishant-sethi/deeplearning.ai

This is my assignment on Andrew Ng's special course "Deep Learning Specialization" This course consists of five courses: Neural Networks and Deep Learning Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization Structuring Machine Learning Projects Convolutional Neural Networks Sequence Models
https://github.com/nishant-sethi/deeplearning.ai

andrew-ng-course artificial-intelligence coursera deep-learning deep-learning-algorithms deep-learning-tutorial deep-neural-networks deeplearning-ai face-recognition jupyter-notebook machine-learning object-detection python tensorflow-experiments

Last synced: 7 days ago
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This is my assignment on Andrew Ng's special course "Deep Learning Specialization" This course consists of five courses: Neural Networks and Deep Learning Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization Structuring Machine Learning Projects Convolutional Neural Networks Sequence Models

• Host: GitHub
• URL: https://github.com/nishant-sethi/deeplearning.ai
• Owner: nishant-sethi
• License: apache-2.0
• Created: 2018-09-23T19:30:17.000Z (about 6 years ago)
• Default Branch: master
• Last Pushed: 2019-03-12T16:33:16.000Z (over 5 years ago)
• Last Synced: 2024-09-23T08:02:33.086Z (11 days ago)
• Topics: andrew-ng-course, artificial-intelligence, coursera, deep-learning, deep-learning-algorithms, deep-learning-tutorial, deep-neural-networks, deeplearning-ai, face-recognition, jupyter-notebook, machine-learning, object-detection, python, tensorflow-experiments
• Language: Jupyter Notebook
• Homepage:
• Size: 53 MB
• Stars: 12
• Watchers: 4
• Forks: 14
• Open Issues: 1
• Metadata Files:
  • Readme: README.md
  • Contributing: CONTRIBUTING.md
  • License: LICENSE
  • Code of conduct: CODE_OF_CONDUCT.md

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README

        
# DeepLearning.ai

This is my assignment on Andrew Ng's special course "Deep Learning Specialization" This course consists of five courses:

Course Contents

Neural Networks and Deep Learning

Week1　Introduction to deep learning

Week2　Neural Networks Basics

Week3　Shallow Neural networks

Week4　Deep Neural Networks

Improving Deep Neural Networks

   

Week1　Practical aspects of Deep Learning(Initialization-Regularization-Gradient Checking)

Week2　Optimization algorithms

Week3　Hyperparameter tuning, Batch Normalization and Programming Frameworks

Convolutional Neural Network

Week1　Foundations of Convolutional Neural Networks

Week2　Deep convolutional models: case studies

Week3　Object detection

Week4　Special applications: Face recognition & Neural style transfer

Sequence Models

Week1　Recurrent Neural Networks

Week2　Natural Language Processing & Word Embeddings

Week3　Sequence models & Attention mechanism