学习笔记 via Jupyter Notebook
深度学习 Deep Learning
神经网络与深度学习 Neural Network and Deep Learning
深度学习简介 Introduction to Deep Learning 神经网络基础 Neural Network Basics 浅层神经网络 Shallow Neural Network 深度神经网络 Deep Neural Network提升深度神经网络 Improving Deep Neural Network
深度学习的使用 Practical aspects of Deep Learning 优化算法 Optimization algorithms 超参调节、批量标准化、编程框架 Hyperparameter tuning, Batch Normalization and Programming Frameworks机器学习 Machine Learning
监督学习 Supervised Learning
线性回归 Linear Regression 逻辑回归 Logistic Regression 广义线性模型 Generalized Linear Models 生成学习算法 Generative Learning Algorithm 支持向量机 Support Vector Machines学习理论 Learning Theory
学习理论 Learning Theory 正则化和模型选择 Regularization and Model Selection 应用机器学习 Advice on Applying Machine Learning非监督学习 Unsupervised Learning
k均值聚类 k-Means Clustering 高斯混合模型 Gaussian Mixture Models EM算法 The EM Algorithm 因子分析 Factor Analysis 主成分分析 Principal Components Analysis 独立成分分析 Independent Components Analysis强化学习 Reinforcement Learning
强化学习和控制 Reinforcement Learning and Control