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| 01. Welcome to Advanced Machine Learning.html |
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| 01. What is Deep Learning .html |
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| 02. K-means clustering of movie ratings.html |
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| 02. Logistic Regression - Question-kSs6O3R7JUI.en-US.vtt |
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| 02. Logistic Regression Quiz.html |
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| 02. Meet Chris-0ccflD9x5WU.ar.vtt |
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| 02. MLND SL DT 01 Recommending Apps 1 MAIN V3-uI_yNrqqKVg.en.vtt |
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| 02. MLND SL EM 02 Bagging V1 MAIN V1-9L_B0Jcio3c.en.vtt |
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| 02. MLND - Unsupervised Learning - L2 02 V1-Ed6RKuBzKWA.en.vtt |
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| 02. Model Complexity Graph.html |
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| 02. Neural Nets as Value Functions.html |
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| 02. OpenAI Gym BlackjackEnv.html |
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| 02. OpenAI Gym CliffWalkingEnv.html |
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| 02. OpenAI Gym FrozenLakeEnv.html |
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| 02. Outline.html |
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| 02. Overview of other clustering methods.html |
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| 02. Policies.html |
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| 02. Prepare for the Udacity Talent Program.html |
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| 02. Program Structure.html |
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| 02. Projects You Will Build.html |
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| 02. Quiz Housing Prices.html |
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| 02. Random Projection.html |
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| 02. Recommending Apps 1.html |
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| 02. Resources.html |
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| 02. RL M2L4 02 A Better Score Function V2-_HBJ3l10-OE.en.vtt |
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| 02. SL NB 01 Guess The Person V1 V1-tAOAjI-7ins.en.vtt |
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| 02. Software Requirements.html |
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| 02. Solving Problems - Big and Small .html |
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| 02. Starting the project.html |
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| 02. Support.html |
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| 02. SVM 01 Which Line Is Better V1-NCml_NCvd1I.en.vtt |
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| 02. The Setting, Revisited.html |
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| 02. Trickier Data Dimensionality.html |
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| 02. Two-Layer Neural Network.html |
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| 02. Use Your Story to Stand Out.html |
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| 02. What You'll Watch and Learn.html |
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| 02. Which line is better.html |
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| 02. Why Policy-Based Methods.html |
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| 03. AdaBoost.html |
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| 03. Apply Credits.html |
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| 03. Bugcrowd.html |
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| 03. Classification Problems 1.html |
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| 03. Clustering Movies.html |
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| 03. Cross Validation.html |
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| 03. Decision Trees Quiz.html |
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| 03. Deep Learning What You'll Do.html |
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| 03. Discrete vs. Continuous Spaces.html |
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| 03. Gaussian Distribution in One Dimension.html |
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| 03. Known and Inferred.html |
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| 03. Submitting the project.html |
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| 14. Minimizing Cross Entropy.html |
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| 15. Implementation.html |
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| 15. MLND - Unsupervised Learning - L2 10 DBSCAN Examples Applications MAIN V1 V2-GhyFsjQ4FkA.en.vtt |
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| 15. MLND - Unsupervised Learning - L3 16 Cluster Analysis Process MAIN V1 V1-aI2wW4fcU1I.en.vtt |
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| 15. More on Sensitivity and Specificity.html |
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| 15. Pooling Layers.html |
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| 18. Outro.html |
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| 20. Optimizing a Logistic Classifier.html |
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