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Welcome to Machine Learning
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What is Machine Learning?
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[Project] Introductory Practice Project (泰坦尼克号乘客生存率分析)
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Nanodegree Career Services
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Evaluation Metrics (评估指标)
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Model Selection (模型选择)
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NumPy and pandas Assessment (自我评估:NumPy和pandas)
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Model Evaluation and Validation Assessment (模型评估与验证 自我评估)
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[Project] 预测您的下一道世界料理
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[Project] 预测波士顿房价
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Linear Regression (线性回归)
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Perceptron Algorithm (感知器算法)
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Decision Trees (决策树)
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Naive Bayes (朴素贝叶斯)
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Support Vector Machines (支持向量机)
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Ensemble Methods (集成方法)
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Supervised Learning Assessment (监督学习 自我评估)
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[Project] 监督学习实战项目
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Clustering (聚类)
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Clustering Mini-Project (聚类迷你项目)
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Hierarchical and Density-based Clustering (层次聚类法与密度聚类)
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Gaussian Mixture Models and Cluster Validation (高斯混合模型与聚类验证)
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Feature Scaling (特征缩放)
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PCA (主成分分析)
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PCA Mini-Project (PCA迷你项目)
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Random Projection and ICA (随机投影与ICA)
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Unsupervised Learning Assessment (非监督学习 自我评估)
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[Project] 创建客户细分
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Neural Networks (神经网络)
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Deep Neural Networks (深度神经网络)
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Convolutional Neural Networks (卷积神经网络)
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Deep Learning for Cancer Detection with Sebastian Thrun (癌症检测深度学习)
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Deep Learning Assessment (深度学习 自我评估)
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[Project] Deep Learning Project (狗狗品种分类)
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Introduction to RL
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The RL Framework: The Problem (强化学习框架:问题)
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The RL Framework: The Solution (强化学习框架:解决方案)
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Dynamic Programming (动态规划)
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Monte Carlo Methods (蒙特卡洛方法)
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Temporal-Difference Methods (时间差分方法)
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[Project] Solve OpenAI Gym's Taxi-v2 Task
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[Project] Q-Learning Maze Project (机器人走迷宫)
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RL in Continuous Spaces (连续空间中的强化学习)
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Deep Q-Learning (深度Q-学习)
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Policy-Based Methods (策略梯度)
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Actor-Critic Methods (行动者-评论者方法)
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Reinforcement Learning Assessment (强化学习 自我评估)
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[Project] 训练四轴飞行器学会飞行
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[Project] 撰写开题报告
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[Project] 毕业项目提交