Completion Certificate for Deep Learning

Completed by Tzu-Heng Lin

March 7, 2018

Approximately 3 months at 10 hours a week to complete

Tzu-Heng Lin's account is verified. Coursera certifies their successful completion of DeepLearning.AI Deep Learning Specialization.

Course Certificates Completed

Neural Networks and Deep Learning

Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

Structuring Machine Learning Projects

Convolutional Neural Networks

Sequence Models

Deep Learning

DeepLearning.AI

4.9 (134,760 ratings)

890K Students Enrolled

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What you will learn

Build and train deep neural networks, identify key architecture parameters, implement vectorized neural networks and deep learning to applications
Train test sets, analyze variance for DL applications, use standard techniques and optimization algorithms, and build neural networks in TensorFlow
Build a CNN and apply it to detection and recognition tasks, use neural style transfer to generate art, and apply algorithms to image and video data
Build and train RNNs, work with NLP and Word Embeddings, and use HuggingFace tokenizers and transformer models to perform NER and Question Answering

Skills you will gain

Recurrent Neural Network
Tensorflow
Convolutional Neural Network
Artificial Neural Network
Transformers

View certificate for Tzu-Heng Lin, Deep Learning, offered through Coursera. Congratulations! You have completed all 5 courses of the Deep Learning Specialization.

In this Specialization, you built neural network architectures such as Convolutional Neural Networks, Recurrent Neural Networks, LSTMs, Transformers, and learned how to make them better with strategies such as Dropout, BatchNorm, and Xavier/He initialization. You mastered these theoretical concepts, learned their industry applications using Python and TensorFlow, and tackled real-world cases such as speech recognition, music synthesis, chatbots, machine translation, natural language processing, and more.

You are now familiar with the capabilities and challenges of deep learning. You are ready to take the definitive step in the world of AI and participate in the development of leading-edge technology.

Course Certificates

Earned after completing each course in the Specialization

Neural Networks and Deep Learning

DeepLearning.AI

Taught by: Andrew Ng, Kian Katanforoosh & Younes Bensouda Mourri

Completed by: Tzu-Heng Lin by October 22, 2017

At the rate of 5 hours a week, it takes roughly 5 weeks to finish each course in the Specialization.

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Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

DeepLearning.AI

Taught by: Andrew Ng, Kian Katanforoosh & Younes Bensouda Mourri

Completed by: Tzu-Heng Lin by October 29, 2017

At the rate of 5 hours a week, it typically takes 5 weeks to complete this course

View this certificate

Structuring Machine Learning Projects

DeepLearning.AI

Taught by: Andrew Ng, Younes Bensouda Mourri & Kian Katanforoosh

Completed by: Tzu-Heng Lin by November 6, 2017

At the rate of 5 hours a week, it typically takes 4 weeks to complete this course

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Convolutional Neural Networks

DeepLearning.AI

Taught by: Andrew Ng, Kian Katanforoosh & Younes Bensouda Mourri

Completed by: Tzu-Heng Lin by March 2, 2018

At the rate of 5 hours a week, it typically takes 5 weeks to complete this course

View this certificate

Sequence Models

DeepLearning.AI

Taught by: Andrew Ng, Kian Katanforoosh & Younes Bensouda Mourri

Completed by: Tzu-Heng Lin by March 7, 2018

At the rate of 5 hours a week, it typically takes 5 weeks to complete this course

View this certificate