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Machine Learning [Week 06/11] Advice for Applying Machine Learning / Machine Learning System Design

See also DL [Course 2/5] Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimizatio […]

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機械学習

Machine Learning [Week 05/11] Neural Networks: Learning

See also DL [Course 1/5] Neural Networks and Deep Learning [Week 1,2/4] Introduction to deep learning / Neural […]

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機械学習

DL [Course 5/5] Sequence Models [Week 3/3] Sequence models & Attention mechanism

Various sequence to sequence architectures Basic Models Sequence to sequence model \(x\): Jane visite l’ […]

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機械学習

DL [Course 5/5] Sequence Models [Week 2/3] Natural Language Processing & Word Embeddings

Introduction to Word Embeddings Word Representation Word representation \[V=[a,aaron,…,zulu,<UNK>] […]

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DL [Course 5/5] Sequence Models [Week 1/3] Recurrent Neural Networks

Why sequence models Examples of sequence data Speech recognition x: wave🌊 y: “The quick brown fox jumped […]

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DL [Course 4/5] Convolutional Neural Networks [Week 4/4] Special applications: Face recognition & Neural style transfer

[mathjax] Face Recognition What is face recognition? Face verification vs. face recognition Verification Input […]

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DL [Course 4/5] Convolutional Neural Networks [Week 3/4] Object detection

Key Concepts Remember the vocabulary of object detection (landmark, anchor, bounding box, grid, …) Under […]

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機械学習

DL [Course 4/5] Convolutional Neural Networks [Week 2/4] Deep convolutional models: case studies

Key Concepts Understand and Implement a Residual network Clone a repository from github and use transfer learn […]

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DL [Course 4/5] Convolutional Neural Networks [Week 1/4] Foundations of Convolutional Neural Networks

Key Concepts Understand the convolution operation Understand the pooling operation Remember the vocabulary use […]

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DL [Course 3/5] Structuring Machine Learning Projects [Week 2/2]

Key Concepts Understand what multi-task learning and transfer learning are Recognize bias, variance and data-m […]