清華大學
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教學發展中心
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開放式課程
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English Version
工程學群
深度學習:吳尚鴻
授課老師
課程大綱
課程內容
第1講 Introduction/Scientific Python 101
第2講 Linear Algebra/Data Exploration & PCA
第3講 Probability & Information Theory/Decision Trees & Random Forest
第4講 Numerical Optimization/ Perceptron & Adaline /Regression
第5講 Learning Theory & Regularization /Regularization
第6講 Probabilistic Models/Logistic Regression & Metrics
第7講 Non-Parametric Methods & SVMs/SVMs & Scikit-Learn Pipelines
第8講 Cross Validation & Ensembling/CV & Ensembling
第9講 Large-Scale Machine Learning
第10講 Neural Networks: Design/ TensorFlow101 & Word2Vec
第11講 Neural Networks: Optimization & Regularization
第12講 Convolutional Neural Networks/Nuts and Bolts of Convolutional Neural Networks/Visualization and Style Transfer
第13講 Recurrent Neural Networks/Seq2Seq Learning for Machine Translation
第14講 Unsupervised Learning/Autoencoders/GANs
第15講 Semisupervised/Transfer Learning and the Future
第16講 Reinforcement Learning/Q-learning
第17講 Deep Reinforcement Learning/ DQN & Policy Network
第1R講 Introduction/Scientific Python 101
第2R講 Linear Algebra/Data Exploration & PCA
第3R講 Probability & Information Theory/Decision Trees & Random Forest
第4R講 Numerical Optimization/ Perceptron & Adaline /Regression
第5R講 Learning Theory & Regularization /Regularization
第6R講 Probabilistic Models/Logistic Regression & Metrics
第7R講 Non-Parametric Methods & SVMs/SVMs & Scikit-Learn Pipelines
第8R講 Cross Validation & Ensembling/CV & Ensembling
第9R講 Large-Scale Machine Learning
第10R講 Neural Networks: Design/ TensorFlow101 & Word2Vec
第11R講 Neural Networks: Optimization & Regularization
第12R講 Convolutional Neural Networks/Nuts and Bolts of Convolutional Neural Networks/Visualization and Style Transfer
第13R講 Recurrent Neural Networks/Seq2Seq Learning for Machine Translation
第14R講 Unsupervised Learning/Autoencoders/GANs
第15R講 Semisupervised/Transfer Learning and the Future
第16R講 Reinforcement Learning/Q-learning
第17R講 Deep Reinforcement Learning/ DQN & Policy Network