[FCO] M.L.Engineer.Nano v2.0.0
File List
- Part 02-Module 04-Lesson 02_Deep Q-Learning/07. Experience Replay-wX_-SZG-YMQ.mp4 48.4 MB
- Part 02-Module 04-Lesson 03_Policy-Based Methods/07. M2L3 07 V2-ZBLLGIN1EfU.mp4 43.5 MB
- Part 01-Module 11-Lesson 04_Gaussian Mixture Models and Cluster Validation/19. MLND - Unsupervised Learning - L3 20 Internal Validation Indices MAIN V1 V2-39JruOTptKI.mp4 40.7 MB
- Part 02-Module 04-Lesson 02_Deep Q-Learning/10. DQN Improvements-Zfdbp93A2GU.mp4 39.4 MB
- Part 02-Module 03-Lesson 05_Monte Carlo Methods/03. MC Prediction State Values-0q2wSWyuBj8.mp4 33.4 MB
- Part 02-Module 04-Lesson 01_RL in Continuous Spaces/01. Deep Reinforcement Learning-GPjK124RU5g.mp4 33.2 MB
- Part 01-Module 11-Lesson 04_Gaussian Mixture Models and Cluster Validation/09. MLND - Unsupervised Learning - L3 09 Expectation Maximization Pt 1 V1 MAIN 1 V2-cf-RLKn5ubA.mp4 32.6 MB
- Part 02-Module 06-Lesson 02_Take 30 Min to Improve your LinkedIn/02. Meet Chris-0ccflD9x5WU.mp4 32.5 MB
- Part 02-Module 04-Lesson 03_Policy-Based Methods/02. M2L3 02 V2-ToS8vXGdODE.mp4 32.5 MB
- Part 01-Module 13-Lesson 01_PCA/31. Eigenfaces Code-LgLYw-G4sLQ.mp4 32.4 MB
- Part 01-Module 11-Lesson 04_Gaussian Mixture Models and Cluster Validation/14. MLND - Unsupervised Learning - L3 15 GMM Examples And Applications MAIN V2 V1-FRoxeLp81Bg.mp4 31.6 MB
- Part 02-Module 03-Lesson 04_Dynamic Programming/14. Policy Improvement-4_adUEK0IHg.mp4 30.4 MB
- Part 02-Module 03-Lesson 06_Temporal-Difference Methods/03. TD Prediction TD(0)-CsD6b0csU7o.mp4 30.1 MB
- Part 02-Module 04-Lesson 01_RL in Continuous Spaces/11. Linear Function Approximation-OJ5wrB7o-pI.mp4 28.7 MB
- Part 02-Module 03-Lesson 04_Dynamic Programming/05. An Iterative Method-AX-hG3KvwzY.mp4 27.6 MB
- Part 01-Module 01-Lesson 01_Welcome to Machine Learning/01. 01 Boas-vindas ao programa IntroduçãoMLND V3-A8AnsR6e75I.mp4 27.0 MB
- Part 01-Module 10-Lesson 05_Support Vector Machines/13. SVM 11 Polynomial Kernel 3 V1-XmbK8OjbX5U.mp4 26.8 MB
- Part 01-Module 11-Lesson 04_Gaussian Mixture Models and Cluster Validation/10. MLND - Unsupervised Learning - L3 10 Expectation Maximization Pt 2 MAIN V1 V2-B_xXd0mFUm4.mp4 26.3 MB
- Part 02-Module 04-Lesson 02_Deep Q-Learning/06. Deep Q Network-GgtR_d1OB-M.mp4 25.7 MB
- Part 02-Module 06-Lesson 01_Optimize Your GitHub Profile/14. Interview with Art - Part 3-M6PKr3S1rPg.mp4 25.0 MB
- Part 01-Module 11-Lesson 03_Hierarchical and Density-based Clustering/04. MLND - Unsupervised Learning - L2 04 Examining SingleLink Clustering MAIN V1 V2-foLcmCOLDos.mp4 23.4 MB
- Part 01-Module 11-Lesson 01_Clustering/13. Sklearn-3zHUAXcoZ7c.mp4 23.3 MB
- Part 01-Module 11-Lesson 04_Gaussian Mixture Models and Cluster Validation/17. MLND - Unsupervised Learning - L3 18 External Validation Indices MAIN V1 V2-rXZM5X2-5D0.mp4 23.2 MB
- Part 01-Module 11-Lesson 03_Hierarchical and Density-based Clustering/05. MLND - Unsupervised Learning - L2 05 CompleteLink AverageLink Ward MAIN V1 V2-dWGQVcZ95d0.mp4 22.5 MB
- Part 02-Module 03-Lesson 05_Monte Carlo Methods/06. MC Prediction Action Values-08tLtbh0xLs.mp4 22.0 MB
- Part 02-Module 03-Lesson 05_Monte Carlo Methods/13. MC Control Policy Improvement-2RKH-BInX7s.mp4 22.0 MB
- Part 02-Module 06-Lesson 01_Optimize Your GitHub Profile/05. Interview with Art - Part 1-ClLYamtaO-Q.mp4 21.8 MB
- Part 01-Module 10-Lesson 03_Decision Trees/01. MLND SL DT 00 Intro V2-l34ijtQhVNk.mp4 21.7 MB
- Part 02-Module 04-Lesson 01_RL in Continuous Spaces/03. Discrete vs. Continuous Spaces-uHstLeRzaE8.mp4 21.4 MB
- Part 01-Module 10-Lesson 04_Naive Bayes/04. SL NB 03 Guess The Person Now V1 V2-pQgO1KF90yU.mp4 21.1 MB
- Part 02-Module 04-Lesson 03_Policy-Based Methods/04. M2L3 04 V1-QicxmyE5vTo.mp4 21.0 MB
- Part 02-Module 04-Lesson 02_Deep Q-Learning/08. Fixed Q Targets-SWpyiEezfp4.mp4 21.0 MB
- Part 01-Module 13-Lesson 01_PCA/28. PCA in sklearn-SBYdqlLgbGk.mp4 20.9 MB
- Part 01-Module 13-Lesson 01_PCA/23. PCA for Feature Transformation-8kUPRUEMCA8.mp4 20.8 MB
- Part 02-Module 03-Lesson 06_Temporal-Difference Methods/01. Introduction-yXErXQulI_o.mp4 20.7 MB
- Part 02-Module 06-Lesson 02_Take 30 Min to Improve your LinkedIn/03. Elevator Pitch-S-nAHPrkQrQ.mp4 20.6 MB
- Part 02-Module 03-Lesson 03_The RL Framework The Solution/02. Policies-hc3LrvaC13U.mp4 20.2 MB
- Part 02-Module 04-Lesson 01_RL in Continuous Spaces/10. Function Approximation-UTGWVY6jEdg.mp4 20.1 MB
- Part 02-Module 03-Lesson 05_Monte Carlo Methods/10. MC Control Incremental Mean-E2RITH-2NUE.mp4 20.1 MB
- Part 01-Module 11-Lesson 03_Hierarchical and Density-based Clustering/11. MLND - Unsupervised Learning - L2 08 DBSCAN MAIN V1 V2--dqyFkfnctI.mp4 20.0 MB
- Part 01-Module 11-Lesson 04_Gaussian Mixture Models and Cluster Validation/11. MLND - Unsupervised Learning - L3 11 Visual Example Of EM Progress MAIN V1 V1-9x3d_eVJrJE.mp4 19.7 MB
- Part 02-Module 04-Lesson 03_Policy-Based Methods/03. M2L3 03 V2-TePX-0Bs23E.mp4 18.9 MB
- Part 01-Module 10-Lesson 05_Support Vector Machines/07. SVM 06 Margin Error V2-dSac8Gfgbok.mp4 18.8 MB
- Part 01-Module 10-Lesson 05_Support Vector Machines/14. SVM 12 RBF Kernel 1 V3-xdkIulxXWfQ.mp4 18.6 MB
- Part 02-Module 02-Lesson 04_Convolutional Neural Networks/17. CNNs For Image Classification-l9vg_1YUlzg.mp4 18.2 MB
- Part 01-Module 11-Lesson 03_Hierarchical and Density-based Clustering/03. MLND - Unsupervised Learning - L2 03 V2-pd9Ix3WMP_Q.mp4 18.1 MB
- Part 01-Module 13-Lesson 01_PCA/17. Composite Features-spVqFnSvlIU.mp4 18.1 MB
- Part 01-Module 11-Lesson 03_Hierarchical and Density-based Clustering/15. MLND - Unsupervised Learning - L2 10 DBSCAN Examples Applications MAIN V1 V2-GhyFsjQ4FkA.mp4 17.8 MB
- Part 02-Module 02-Lesson 04_Convolutional Neural Networks/02. Aplicações de CNNs-HrYNL_1SV2Y.mp4 17.7 MB
- Part 01-Module 13-Lesson 01_PCA/29. When to Use PCA-hJZHcmJBk1o.mp4 17.5 MB
- Part 02-Module 04-Lesson 02_Deep Q-Learning/09. Deep Q-Learning Algorithm-MqTXoCxQ_eY.mp4 17.4 MB
- Part 02-Module 06-Lesson 02_Take 30 Min to Improve your LinkedIn/01. Why Network-exjEm9Paszk.mp4 17.4 MB
- Part 02-Module 04-Lesson 02_Deep Q-Learning/05. Q-Learning-AI5gLgYMSq8.mp4 17.3 MB
- Part 02-Module 02-Lesson 04_Convolutional Neural Networks/11. Camadas convolucionais-RnM1D-XI--8.mp4 17.1 MB
- Part 02-Module 04-Lesson 02_Deep Q-Learning/04. Temporal Difference Learning-lpmDi0QeUm8.mp4 17.0 MB
- Part 02-Module 04-Lesson 04_Actor-Critic Methods/07. Summary-hvYQ_3LgCYs.mp4 16.9 MB
- Part 02-Module 04-Lesson 03_Policy-Based Methods/05. M2L3 05 V1-eZxxNNIZuwA.mp4 16.6 MB
- Part 02-Module 03-Lesson 06_Temporal-Difference Methods/10. TD Control Sarsamax-4DxoYuR7aZ4.mp4 16.5 MB
- Part 01-Module 01-Lesson 02_What is Machine Learning/01. Introduction-bYeteZQrUcE.mp4 16.0 MB
- Part 02-Module 03-Lesson 04_Dynamic Programming/23. Value Iteration-XNeQn8N36y8.mp4 15.6 MB
- Part 01-Module 11-Lesson 03_Hierarchical and Density-based Clustering/01. MLND - Unsupervised Learning - L2 01 V2-NHb8w_M8nDY.mp4 15.5 MB
- Part 03-Module 03-Lesson 01_Intro to Neural Networks/04. Neural Networks-Mqogpnp1lrU.mp4 14.9 MB
- Part 01-Module 12-Lesson 01_Feature Scaling/11. MinMax Scaler in sklearn-lgoh5R05YM0.mp4 14.9 MB
- Part 02-Module 03-Lesson 02_The RL Framework The Problem/17. MDPs, Part 3-UlXHFbla3QI.mp4 14.7 MB
- Part 01-Module 10-Lesson 04_Naive Bayes/07. SL NB 06 S False Positives V1 V3-Bg6_Tvcv81A.mp4 14.4 MB
- Part 01-Module 05-Lesson 01_Training and Testing Models/09. Testing-gmxGRJSKEb0.mp4 14.3 MB
- Part 02-Module 03-Lesson 02_The RL Framework The Problem/11. Discounted Return-opXGNPwwn7g.mp4 14.3 MB
- Part 02-Module 03-Lesson 04_Dynamic Programming/20. Truncated Policy Iteration-a-RvCxlPMho.mp4 14.1 MB
- Part 02-Module 02-Lesson 04_Convolutional Neural Networks/25. Transfer Learning-LHG5FltaR6I.mp4 13.3 MB
- Part 01-Module 13-Lesson 01_PCA/20. Maximal Variance and Information Loss-hfmvk8DzTGA.mp4 13.3 MB
- Part 01-Module 01-Lesson 02_What is Machine Learning/21. K-means Clustering-pv_i08zjpQw.mp4 13.2 MB
- Part 02-Module 06-Lesson 01_Optimize Your GitHub Profile/10. Interview with Art - Part 2-Vvzl2J5K7-Y.mp4 13.2 MB
- Part 01-Module 10-Lesson 03_Decision Trees/14. Maximizing Information Gain-3FgJOpKfdY8.mp4 13.1 MB
- Part 01-Module 10-Lesson 05_Support Vector Machines/05. SVM 04 Perceptron Algorithm V1-IIlQHBOrD6Q.mp4 12.9 MB
- Part 02-Module 02-Lesson 04_Convolutional Neural Networks/26. Transfer Learning in Keras-HsIAznMM1LA.mp4 12.9 MB
- Part 01-Module 01-Lesson 02_What is Machine Learning/04. Decision Trees Answer-h8zH47iFhCo.mp4 12.7 MB
- Part 01-Module 11-Lesson 01_Clustering/02. Unsupervised Learning-Mx9f99bRB3Q.mp4 12.7 MB
- Part 02-Module 04-Lesson 02_Deep Q-Learning/02. Neural Nets as Value Functions-cBi7vLrk8QQ.mp4 12.7 MB
- Part 01-Module 13-Lesson 01_PCA/25. ReviewDefinition of PCA-oFBGXUUuKyI.mp4 12.6 MB
- Part 01-Module 10-Lesson 03_Decision Trees/07. Entropy-piLpj1V1HEk.mp4 12.6 MB
- Part 01-Module 10-Lesson 05_Support Vector Machines/06. SVM 05 Classification Error V1-nWGVAGXwvGE.mp4 12.6 MB
- Part 02-Module 04-Lesson 01_RL in Continuous Spaces/05. Discretization-j2eZyUpy--E.mp4 12.5 MB
- Part 01-Module 13-Lesson 01_PCA/16. Compression While Preserving Information-NjuenhkC-44.mp4 12.5 MB
- Part 02-Module 03-Lesson 05_Monte Carlo Methods/18. MC Control Constant-alpha-QFV1nI9Zpoo.mp4 12.5 MB
- Part 01-Module 10-Lesson 03_Decision Trees/09. MLND SL DT 08 Entropy Formula 2 MAIN V2-6GHg70hrSJw.mp4 12.3 MB
- Part 01-Module 12-Lesson 01_Feature Scaling/12. Quiz on Algorithms Requiring Rescaling-oEhevl5DWpk.mp4 12.1 MB
- Part 02-Module 02-Lesson 04_Convolutional Neural Networks/09. Local Connectivity-z9wiDg0w-Dc.mp4 12.0 MB
- Part 01-Module 11-Lesson 04_Gaussian Mixture Models and Cluster Validation/15. MLND - Unsupervised Learning - L3 16 Cluster Analysis Process MAIN V1 V1-aI2wW4fcU1I.mp4 11.7 MB
- Part 01-Module 13-Lesson 01_PCA/18. Maximal Variance-tfYAGBIR_Ws.mp4 11.5 MB
- Part 01-Module 12-Lesson 01_Feature Scaling/06. Comparing Features with Different Scales-PRL8trOU7Rs.mp4 11.5 MB
- Part 03-Module 03-Lesson 01_Intro to Neural Networks/11. Gradient Descent-Math-7sxA5Ap8AWM.mp4 11.3 MB
- Part 02-Module 04-Lesson 01_RL in Continuous Spaces/07. Tile Coding-BRs7AnTZ_8k.mp4 11.0 MB
- Part 01-Module 13-Lesson 01_PCA/30. PCA for Facial Recognition-WyoU2otqsd8.mp4 10.8 MB
- Part 02-Module 04-Lesson 04_Actor-Critic Methods/05. RL M2L4 05 Advantage Function RENDER V1 V2-vpLmzKqcgfc.mp4 10.7 MB
- Part 01-Module 11-Lesson 01_Clustering/11. K-Means Clustering Visualization 2-fQXXa-CAoS0.mp4 10.5 MB
- Part 02-Module 04-Lesson 02_Deep Q-Learning/03. Monte Carlo Learning-qOviWYwcvsg.mp4 10.4 MB
- Part 02-Module 04-Lesson 04_Actor-Critic Methods/01. RL M2L4 01 Actor Critic Methods RENDER V1 V1-FXhyxJzgt8U.mp4 10.4 MB
- Part 01-Module 13-Lesson 01_PCA/21. Info Loss and Principal Components-LTPV8lxQeZQ.mp4 10.3 MB
- Part 02-Module 04-Lesson 01_RL in Continuous Spaces/09. Coarse Coding-Uu1J5KLAfTU.mp4 10.3 MB
- Part 02-Module 02-Lesson 04_Convolutional Neural Networks/20. Image Augmentation in Keras-odStujZq3GY.mp4 10.3 MB
- Part 01-Module 11-Lesson 04_Gaussian Mixture Models and Cluster Validation/04. MLND - Unsupervised Learning - L3 04 GMM Clustering In 1D MAIN V1 V1-JkRQIGqkqA4.mp4 10.3 MB
- Part 01-Module 01-Lesson 02_What is Machine Learning/05. Naive Bayes Quiz-jsLkVYXmr3E.mp4 10.1 MB
- Part 02-Module 03-Lesson 02_The RL Framework The Problem/03. Episodic vs. Continuing Tasks-E1I-BPanSM8.mp4 10.1 MB
- Part 02-Module 04-Lesson 04_Actor-Critic Methods/04. RL M2L4 04 The Actor And The Critic V1-bvbE9F7urd4.mp4 10.0 MB
- Part 02-Module 06-Lesson 02_Take 30 Min to Improve your LinkedIn/04. Elevator Pitch-0QtgTG49E9I.mp4 10.0 MB
- Part 02-Module 03-Lesson 02_The RL Framework The Problem/10. Cumulative Reward-ysriH65lV9o.mp4 10.0 MB
- Part 02-Module 04-Lesson 01_RL in Continuous Spaces/14. Summary-MTEBk43oByU.mp4 9.9 MB
- Part 01-Module 15-Lesson 01_Random Projection and ICA/10. L6 6 ICA Applications MAIN V1 V1 V1-th12mTv1B7g.mp4 9.9 MB
- Part 01-Module 01-Lesson 02_What is Machine Learning/16. Neural Networks-xFu1_2K2D2U.mp4 9.8 MB
- Part 01-Module 01-Lesson 02_What is Machine Learning/23. Conclusion-hJEuaOUu2yA.mp4 9.7 MB
- Part 02-Module 03-Lesson 06_Temporal-Difference Methods/06. TD Prediction Action Values-1c029-7_9GA.mp4 9.7 MB
- Part 01-Module 10-Lesson 05_Support Vector Machines/12. SVM 10 Polynomial Kernel 2 V2-9RfFvZ9DIRg.mp4 9.7 MB
- Part 02-Module 06-Lesson 01_Optimize Your GitHub Profile/02. Introduction-Vnj2VNQROtI.mp4 9.6 MB
- Part 02-Module 03-Lesson 01_Introduction to RL/04. OpenAI Gym-MktEOWp3QLg.mp4 9.5 MB
- Part 01-Module 10-Lesson 04_Naive Bayes/10. SL NB 09 Bayesian Learning 3 V1 V4-u-Hj4RsJn1o.mp4 9.3 MB
- Part 01-Module 10-Lesson 05_Support Vector Machines/16. SVM 14 RBF Kernel 3 V1-DctkE8kaWPY.mp4 9.3 MB
- Part 01-Module 10-Lesson 03_Decision Trees/13. Information Gain-k9iZL53PAmw.mp4 9.2 MB
- Part 01-Module 07-Lesson 01_Model Selection/03. Model-Complexity-Graph Solution 2-5pWHGkNyRhA.mp4 9.2 MB
- Part 01-Module 15-Lesson 01_Random Projection and ICA/01. L6 1 Random Projection MAIN V1 V1 V1-Iat1a8mzI-Y.mp4 9.2 MB
- Part 01-Module 10-Lesson 03_Decision Trees/15. MLND SL DT 13 Random Forests MAIN V1-n5DhXhcYKcw.mp4 9.2 MB
- Part 02-Module 02-Lesson 04_Convolutional Neural Networks/23. Visualizando CNNs-mnqS_EhEZVg.mp4 9.2 MB
- Part 03-Module 02-Lesson 01_Intro to TensorFlow/02. Solving Problems - Big And Small-WHcRQMGSbqg.mp4 9.2 MB
- Part 01-Module 11-Lesson 03_Hierarchical and Density-based Clustering/09. MLND - Unsupervised Learning - L2 07 HC Examples Applications MAIN V1 V2-HTahFoQwk2g.mp4 9.2 MB
- Part 02-Module 03-Lesson 05_Monte Carlo Methods/12. MC Control Policy Evaluation-3_opwMzpEEI.mp4 9.1 MB
- Part 02-Module 04-Lesson 02_Deep Q-Learning/01. Intro to Deep Q-Learning-o3cmuUDhP3I.mp4 9.1 MB
- Part 02-Module 06-Lesson 02_Take 30 Min to Improve your LinkedIn/04. Pitching to a Recruiter-LxAdWaA-qTQ.mp4 8.9 MB
- Part 02-Module 04-Lesson 01_RL in Continuous Spaces/12. Kernel Functions-RdkPVYyVOvU.mp4 8.9 MB
- Part 01-Module 10-Lesson 01_Linear Regression/22. Regularization-PyFNIcsNma0.mp4 8.8 MB
- Part 02-Module 02-Lesson 04_Convolutional Neural Networks/18. CNNs in Keras Practical Example-faFvmGDwXX0.mp4 8.7 MB
- Part 02-Module 04-Lesson 04_Actor-Critic Methods/02. RL M2L4 02 A Better Score Function V2-_HBJ3l10-OE.mp4 8.7 MB
- Part 01-Module 10-Lesson 04_Naive Bayes/02. SL NB 01 Guess The Person V1 V1-tAOAjI-7ins.mp4 8.5 MB
- Part 03-Module 04-Lesson 01_Deep Neural Networks/01. Mat HS-9P7UPWFu8w8.mp4 8.5 MB
- Part 02-Module 03-Lesson 01_Introduction to RL/02. Applications-CV6B84mKRNM.mp4 8.5 MB
- Part 01-Module 01-Lesson 02_What is Machine Learning/22. Hierarchical Clustering-1PldDT8AwMA.mp4 8.5 MB
- Part 03-Module 05-Lesson 01_Convolutional Neural Networks/04. Convolutional Networks-ISHGyvsT0QY.mp4 8.4 MB
- Part 01-Module 11-Lesson 04_Gaussian Mixture Models and Cluster Validation/03. MLND - Unsupervised Learning - L3 3 Gaussian Distribution In 1D MAINv1 V1-uDPFrZwsKKQ.mp4 8.4 MB
- Part 01-Module 11-Lesson 04_Gaussian Mixture Models and Cluster Validation/01. MLND - Unsupervised Learning - L3 01 Gaussian Mixture Model MAINv1 V3-SLdZrt0CvOk.mp4 8.4 MB
- Part 03-Module 04-Lesson 01_Deep Neural Networks/08. Regularization Intro-pECnr-5F3_Q.mp4 8.3 MB
- Part 02-Module 02-Lesson 05_Deep Learning for Cancer Detection with Sebastian Thrun/26. Conclusion-WhpE_8sTt-0.mp4 8.2 MB
- Part 02-Module 03-Lesson 04_Dynamic Programming/17. Policy Iteration-gqv7o1kBDc0.mp4 8.1 MB
- Part 01-Module 11-Lesson 01_Clustering/16. Counterintuitive Clusters-StmEUgT1XSY.mp4 8.1 MB
- Part 02-Module 02-Lesson 04_Convolutional Neural Networks/22. Groundbreaking CNN Architectures-ddrB-mhMfkY.mp4 8.1 MB
- Part 02-Module 03-Lesson 02_The RL Framework The Problem/08. Goals and Rewards, Part 2-pVIFc72VYH8.mp4 8.0 MB
- Part 02-Module 02-Lesson 04_Convolutional Neural Networks/10. Convolutional Layers-h5R_JvdUrUI.mp4 8.0 MB
- Part 01-Module 10-Lesson 03_Decision Trees/10. Entropy Formula-w73JTBVeyjE.mp4 8.0 MB
- Part 02-Module 02-Lesson 04_Convolutional Neural Networks/12. Stride and Padding-0r9o8hprDXQ.mp4 8.0 MB
- Part 01-Module 15-Lesson 01_Random Projection and ICA/05. L6 4 ICA Algorithm V2 V1-xlhd5UWk_-E.mp4 8.0 MB
- Part 01-Module 13-Lesson 01_PCA/06. PCA for Data Transformation-nDuo5ECT1G4.mp4 7.9 MB
- Part 02-Module 03-Lesson 01_Introduction to RL/03. The Setting-nh8Gwdu19nc.mp4 7.8 MB
- Part 01-Module 13-Lesson 01_PCA/15. From Four Features to Two-MEtIAGKweXU.mp4 7.7 MB
- Part 02-Module 04-Lesson 03_Policy-Based Methods/08. M2L3 08 V1-og3W6CXn1F0.mp4 7.6 MB
- Part 02-Module 03-Lesson 06_Temporal-Difference Methods/07. TD Control Sarsa(0)-LkFkjfsRpXc.mp4 7.6 MB
- Part 02-Module 02-Lesson 03_Deep Neural Networks/13. Regularization-ndYnUrx8xvs.mp4 7.6 MB
- Part 02-Module 03-Lesson 02_The RL Framework The Problem/img/chess-game.jpg 7.5 MB
- Part 02-Module 02-Lesson 01_Neural Networks/02. Introduction-tn-CrUTkCUc.mp4 7.5 MB
- Part 01-Module 11-Lesson 03_Hierarchical and Density-based Clustering/06. MLND - Unsupervised Learning - L2 06 Hierarchical Clustering Implementation MAIN V1 V1-tRqKsk5M9Mc.mp4 7.5 MB
- Part 03-Module 05-Lesson 01_Convolutional Neural Networks/29. Inception Module-SlTm03bEOxA.mp4 7.5 MB
- Part 02-Module 03-Lesson 04_Dynamic Programming/08. M1 L1 C05 V3 No Slack-OH-fVUpoyZDyGE.mp4 7.5 MB
- Part 03-Module 03-Lesson 01_Intro to Neural Networks/03. Logistic Regression - Solution-1iNylA3fJDs.mp4 7.4 MB
- Part 02-Module 03-Lesson 02_The RL Framework The Problem/02. The Setting, Revisited-V6Q1uF8a6kA.mp4 7.4 MB
- Part 01-Module 11-Lesson 01_Clustering/03. Clustering Movies-g8PKffm8IRY.mp4 7.3 MB
- Part 01-Module 11-Lesson 01_Clustering/17. Counterintuitive Clusters 2-HyjBus7S2gY.mp4 7.2 MB
- Part 01-Module 10-Lesson 04_Naive Bayes/05. SL NB 04 Bayes Theorem V1 V2-nVbPJmf53AI.mp4 7.2 MB
- Part 02-Module 02-Lesson 01_Neural Networks/14. Error Functions-jfKShxGAbok.mp4 7.2 MB
- Part 02-Module 04-Lesson 02_Deep Q-Learning/13. Wrap Up-x6JggcDTcys.mp4 7.2 MB
- Part 02-Module 03-Lesson 03_The RL Framework The Solution/11. Optimal Policies-2rguYpVyCto.mp4 7.1 MB
- Part 01-Module 10-Lesson 05_Support Vector Machines/11. SVM 09 Polynomial Kernel 1 V1-8t2tVDHNBnk.mp4 7.1 MB
- Part 01-Module 10-Lesson 05_Support Vector Machines/10. SVM 08 The C Parameter V2-6CxPhVo0hRw.mp4 7.0 MB
- Part 01-Module 13-Lesson 01_PCA/05. Trickiest Data Dimensionality-mTcuS5jUeUE.mp4 7.0 MB
- Part 01-Module 11-Lesson 04_Gaussian Mixture Models and Cluster Validation/05. MLND - Unsupervised Learning - L3 05 Gaussian Distribution In 2D MAIN V1 V2-Ne-qRjO38qQ.mp4 7.0 MB
- Part 01-Module 13-Lesson 01_PCA/30. PCA for Facial Recognition-B_JKtLN-i5I.mp4 7.0 MB
- Part 02-Module 03-Lesson 01_Introduction to RL/05. Resources-_YPqfAnCqtk.mp4 7.0 MB
- Part 02-Module 03-Lesson 05_Monte Carlo Methods/09. Generalized Policy Iteration-XRmz4nolEsw.mp4 6.9 MB
- Part 02-Module 06-Lesson 01_Optimize Your GitHub Profile/09. Writing READMEs with Walter-DQEfT2Zq5_o.mp4 6.9 MB
- Part 01-Module 11-Lesson 01_Clustering/12. K-Means Clustering Visualization 3-WfwX3B4d8_I.mp4 6.9 MB
- Part 02-Module 03-Lesson 02_The RL Framework The Problem/07. Goals and Rewards, Part 1-XPnj3Ya3EuM.mp4 6.8 MB
- Part 02-Module 03-Lesson 02_The RL Framework The Problem/14. MDPs, Part 2-CUTtQvxKkNw.mp4 6.8 MB
- Part 01-Module 13-Lesson 01_PCA/19. Advantages of Maximal Variance-jQaYAlZ1fp0.mp4 6.8 MB
- Part 01-Module 13-Lesson 01_PCA/12. Which Data is Ready for PCA-Su7kIUVPu6w.mp4 6.7 MB
- Part 01-Module 06-Lesson 01_Evaluation Metrics/12. ROC Curve-2Iw5TiGzJI4.mp4 6.7 MB
- Part 02-Module 02-Lesson 05_Deep Learning for Cancer Detection with Sebastian Thrun/18. ROC Curve-2Iw5TiGzJI4.mp4 6.7 MB
- Part 01-Module 12-Lesson 01_Feature Scaling/01. Chris's T-Shirt Size (Intuition)-oaqjLyiKOIA.mp4 6.6 MB
- Part 02-Module 02-Lesson 01_Neural Networks/21. CrossEntropy V1-1BnhC6e0TFw.mp4 6.6 MB
- Part 02-Module 03-Lesson 03_The RL Framework The Solution/09. Action-Value Functions-KJLaRfOOPGA.mp4 6.6 MB
- Part 01-Module 07-Lesson 01_Model Selection/01. 04 L Types Of Errors-Twf1qnPZeSY.mp4 6.6 MB
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- Part 01-Module 01-Lesson 02_What is Machine Learning/12. Logistic Regression Answer-JuAJd9Qvs6U.mp4 6.1 MB
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- Part 01-Module 12-Lesson 01_Feature Scaling/02. A Metric for Chris-O0bvLU4l0is.mp4 4.0 MB
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- Part 01-Module 13-Lesson 01_PCA/09. Second Principal Component Of New System-PqtW_Ux2_nY.mp4 4.0 MB
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- Part 03-Module 03-Lesson 01_Intro to Neural Networks/01. Introducing Luis-nto-stLuN6M.mp4 3.6 MB
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- Part 01-Module 01-Lesson 02_What is Machine Learning/15. SVM Answer-JrUtTwfnsfM.mp4 3.3 MB
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- Part 03-Module 05-Lesson 01_Convolutional Neural Networks/28. 1x1 Convolutions-Zmzgerm6SjA.mp4 3.2 MB
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- Part 01-Module 11-Lesson 03_Hierarchical and Density-based Clustering/02. MLND - Unsupervised Learning - L2 02 V1-Ed6RKuBzKWA.mp4 3.1 MB
- Part 02-Module 02-Lesson 05_Deep Learning for Cancer Detection with Sebastian Thrun/25. Confusion Matrix-3rpN-YYlfes.mp4 3.1 MB
- Part 02-Module 06-Lesson 01_Optimize Your GitHub Profile/12. Reflect on your commit messages-_0AHmKkfjTo.mp4 3.0 MB
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- Part 01-Module 01-Lesson 02_What is Machine Learning/11. Logistic Regression Question-wQXKdeVHTmc.mp4 3.0 MB
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- Part 02-Module 03-Lesson 02_The RL Framework The Problem/01. Introduction-X_9l_ZqXXBA.mp4 2.9 MB
- Part 02-Module 02-Lesson 04_Convolutional Neural Networks/img/screen-shot-2016-11-24-at-12.08.11-pm.png 2.9 MB
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- Part 01-Module 10-Lesson 02_Perceptron Algorithm/09. Perceptron Algorithm Pseudocode-p8Q3yu9YqYk.mp4 2.9 MB
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- Part 01-Module 13-Lesson 01_PCA/22. Neighborhood Composite Feature-adXoa85rnPM.mp4 2.8 MB
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- Part 02-Module 03-Lesson 07_Solve OpenAI Gym's Taxi-v2 Task/img/open-agent-monitor-main.gif 2.7 MB
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- Part 02-Module 02-Lesson 05_Deep Learning for Cancer Detection with Sebastian Thrun/21. ROC Curve-fWwe_JlpnlQ.mp4 2.7 MB
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- Part 02-Module 02-Lesson 03_Deep Neural Networks/29. Conclusion-wOiUQDgGD9E.mp4 2.6 MB
- Part 01-Module 10-Lesson 01_Linear Regression/09. Mean Absolute Error-vLKiY0Ehors.mp4 2.6 MB
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- Part 01-Module 12-Lesson 01_Feature Scaling/12. Quiz on Algorithms Requiring Rescaling-ntRkOeSZutw.mp4 2.5 MB
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- Part 01-Module 13-Lesson 01_PCA/14. Measurable vs. Latent Features Quiz-UeSD19oit_w.mp4 2.5 MB
- Part 01-Module 12-Lesson 01_Feature Scaling/09. Feature Scaling Formula Quiz 3-iY_sO4d23gY.mp4 2.5 MB
- Part 03-Module 03-Lesson 01_Intro to Neural Networks/10. Gradient Descent-29PmNG7fuuM.mp4 2.5 MB
- Part 01-Module 01-Lesson 02_What is Machine Learning/08. Gradient Descent-BEC0uH1fuGU.mp4 2.5 MB
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