Deep Learning Specialization

Deep Learning Specialization

In five courses, the program teaches the foundations of Deep Learning, understand how to build neural networks, and learn how to lead successful machine learning projects. This includes Convolutional networks, RNNs, LSTM, Adam, Dropout, BatchNorm, Xavier/He initialization, and more. Working on case studies from healthcare, autonomous driving, sign language reading, music generation, and natural language processing, onc masters not only the theory, but also sees how it is applied in industry. Ideas are practiced using Python and in TensorFlow, which is taught.

There are also interviews from many top leaders in Deep Learning, who will share their personal stories and offer career advice.

The program is designed to master Deep Learning, understand how to apply it, and build a career in AI.

The 5 courses include:

  1. Neural Networks and Deep Learning
  2. Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization
  3. Structuring Machine Learning Projects
  4. Convolutional Neural Networks
  5. Sequence Models

The cards below have my certification and license information.

Deep Learning Specialization title

Deep Learning Specialization

deeplearning.ai

Certification

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September 2018

Neural Networks & Deep Learning

Neural Networks & Deep Learning

deeplearning.ai

Certification

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September 2018

Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization

Hyperparameters & Regularization

deeplearning.ai

Certification

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September 2018

Structuring Machine Learning Projects

Structuring Machine Learning Projects

deeplearning.ai

Certification

certified badge

September 2018

Convolutional Neural Networks

Convolutional Neural Networks

deeplearning.ai

Certification

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September 2018

Sequence Models

Sequence
Models

deeplearning.ai

Certification

certified badge

September 2018