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Part 03-Module 01-Lesson 06_Matrices and Transformation of State/03. QUIZ Another Prediction 02 RENDER V1-RfzQ5MbVNeQ.mp4273.59KB

Part 05-Module 01-Lesson 02_Training Neural Networks/10. Random Restart-idyBBCzXiqg.mp4394.99KB

Part 06-Module 01-Lesson 01_Deep Learning for Cancer Detection with Sebastian Thrun/18. Images-1GdiN5Wc8LA.mp4395.42KB

Part 03-Module 01-Lesson 04_Introduction to Kalman Filters/11. KALMAN QUIZ Shifting The Mean 02 RENDER V1-L8vNIKvpJ1s.mp4451.32KB

Part 03-Module 01-Lesson 02_Robot Localization/10. 11 Normalize Distribution V1-ZGvmFn_u56o.mp4522.8KB

Part 03-Module 01-Lesson 06_Matrices and Transformation of State/02. QUIZ Kalman Filter Prediction 02 RENDER V2-OelWLjfdSyw.mp4526.05KB

Part 03-Module 01-Lesson 07_Simultaneous Localization and Mapping/10. 10 Untouched Fields QUIZ RENDER V2-V9qbWSqqKwg.mp4540.98KB

Part 03-Module 01-Lesson 04_Introduction to Kalman Filters/15. KALMAN QUIZ Parameter Update 02 RENDER V2-vl6GkkEgY4M.mp4574.57KB

Part 03-Module 01-Lesson 07_Simultaneous Localization and Mapping/07. 07 Adding Landmarks Solution V1-vDfQNdUSclA.mp4609.67KB

Part 02-Module 01-Lesson 04_ Long Short-Term Memory Networks (LSTMs)/08. Remember Gate-0qlm86HaXuU.mp4676.91KB

Part 03-Module 01-Lesson 04_Introduction to Kalman Filters/13. KALMAN QUIZ Predicting The Peak 02 RENDER V1-mcwr6FcP2Vc.mp4677.46KB

Part 03-Module 01-Lesson 02_Robot Localization/21. 18 Exact Motion V1-mNXm1wjTumY.mp4708.57KB

Part 03-Module 01-Lesson 04_Introduction to Kalman Filters/12. KALMAN QUIZ Predicting The Peak 01 RENDER V1-_fGH3xJMxdM.mp4768.11KB

Part 03-Module 01-Lesson 07_Simultaneous Localization and Mapping/06. 06 Adding Landmarks Quiz V1-_JUCLtoh1CE.mp4793.62KB

Part 05-Module 01-Lesson 02_Training Neural Networks/09. Local Minima-gF_sW_nY-xw.mp4819.86KB

Part 06-Module 01-Lesson 01_Deep Learning for Cancer Detection with Sebastian Thrun/07. 07 Quiz Data Challenges V1-F8yc7BlV93c.mp4862.5KB

Part 08-Module 01-Lesson 01_Fully-Convolutional Neural Networks & Semantic Segmentation/05. Transposed Convolutions-K6mlLX8ZZDs.mp4870.48KB

Part 03-Module 01-Lesson 07_Simultaneous Localization and Mapping/05. 05 Implementing Constraints Solution V1-uLmGavXEN64.mp4885.75KB

Part 06-Module 01-Lesson 01_Deep Learning for Cancer Detection with Sebastian Thrun/13. 13 Quiz Sensitivity And Specificty V3-O17MnhWBmKA.mp4888.58KB

Part 03-Module 01-Lesson 02_Robot Localization/31. Move 1000 - Artificial Intelligence for Robotics-x2o1g3J-1nw.mp4922.19KB

Part 05-Module 01-Lesson 02_Training Neural Networks/14. Learning Rate-TwJ8aSZoh2U.mp4927.05KB

Part 05-Module 01-Lesson 01_Feedforward and Backpropagation/02. Why Neural Networks-zAkzOZntK6Y.mp4982.27KB

Part 03-Module 01-Lesson 07_Simultaneous Localization and Mapping/09. 09 Matrix Modification Solution V1-ntK0oz35VPQ.mp4988.79KB

Part 05-Module 01-Lesson 02_Training Neural Networks/06. DL 53 Q Regularization-KxROxcRsHL8.mp41.01MB

Part 02-Module 01-Lesson 04_ Long Short-Term Memory Networks (LSTMs)/07. Forget Gate-iWxpfxLUPSU.mp41.04MB

Part 03-Module 01-Lesson 07_Simultaneous Localization and Mapping/08. 08 Matrix Modification Quiz V1-e3zpWlM9IRg.mp41.06MB

Part 02-Module 01-Lesson 04_ Long Short-Term Memory Networks (LSTMs)/04. LSTM Architecture-ycwthhdx8ws.mp41.07MB

Part 06-Module 01-Lesson 01_Deep Learning for Cancer Detection with Sebastian Thrun/19. 17 Quiz ROC Curve 1 PT2 V1-Xv3v59_CfEU.mp41.11MB

Part 06-Module 01-Lesson 01_Deep Learning for Cancer Detection with Sebastian Thrun/20. Solution ROC Curve-sdUUf6RRmXI.mp41.11MB

Part 03-Module 01-Lesson 05_Representing State and Motion/02. Intro To State-zfilXYrW4Gk.mp41.13MB

Part 06-Module 01-Lesson 01_Deep Learning for Cancer Detection with Sebastian Thrun/16. 15 Quiz Diagnosing Cancer V3-4UzkwecBJro.mp41.14MB

Part 06-Module 01-Lesson 01_Deep Learning for Cancer Detection with Sebastian Thrun/28. Mini Project Introduction-Rgf3YVFWl-M.mp41.15MB

Part 08-Module 01-Lesson 01_Fully-Convolutional Neural Networks & Semantic Segmentation/04. Fully Connected to 1x1 Convolution-xbPtOhkJW1A.mp41.15MB

Part 03-Module 01-Lesson 02_Robot Localization/29. 24 Limit Distribution Quiz V3-NJvalJwjz18.mp41.15MB

Part 09-Module 01-Lesson 05_Python and C++ Speed/01. Introduction-JklGKdn3_go.mp41.19MB

Part 03-Module 01-Lesson 04_Introduction to Kalman Filters/20. Predict Function - Artificial Intelligence for Robotics-DV2cX9W0tT8.mp41.2MB

Part 08-Module 01-Lesson 01_Fully-Convolutional Neural Networks & Semantic Segmentation/08. Bounding Boxes-uPv4d0Xl8hc.mp41.2MB

Part 03-Module 01-Lesson 07_Simultaneous Localization and Mapping/17. 15 Introducing Noise QUIZ RENDER V1-E_OI5DinFA0.mp41.23MB

Part 06-Module 01-Lesson 01_Deep Learning for Cancer Detection with Sebastian Thrun/09. Training The Neural Network-HwiI-UXUx-M.mp41.24MB

Part 01-Module 01-Lesson 01_Welcome to Computer Vision/10. Moving Forward V4-E35QVmp1f2k.mp41.26MB

Part 05-Module 01-Lesson 02_Training Neural Networks/11. Vanishing Gradient-W_JJm_5syFw.mp41.32MB

Part 03-Module 01-Lesson 04_Introduction to Kalman Filters/22. Predict Function Solution - Artificial Intelligence for Robotics-AMFig-sYGfM.mp41.37MB

Part 02-Module 01-Lesson 03_RNN's/09. Regra da cadeia-YAhIBOnbt54.mp41.46MB

Part 05-Module 01-Lesson 01_Feedforward and Backpropagation/05. Chain Rule-YAhIBOnbt54.mp41.46MB

Part 06-Module 01-Lesson 01_Deep Learning for Cancer Detection with Sebastian Thrun/06. 06 Image Challenge V3-Efnoj1KNPHw.mp41.46MB

Part 02-Module 01-Lesson 05_Hyperparameters/06. Number Of Iterations-TTdHpSb4DV8.mp41.46MB

Part 08-Module 01-Lesson 01_Fully-Convolutional Neural Networks & Semantic Segmentation/07. FCNs In The Wild-q9wTd53-hsw.mp41.47MB

Part 06-Module 01-Lesson 01_Deep Learning for Cancer Detection with Sebastian Thrun/08. Solution Data Challenges-1z3o4niQuNg.mp41.49MB

Part 02-Module 01-Lesson 04_ Long Short-Term Memory Networks (LSTMs)/09. LSTM 7 Use Gate-5Ifolm1jTdY.mp41.5MB

Part 03-Module 01-Lesson 07_Simultaneous Localization and Mapping/11. 11 Untouched Fields Solution RENDER V2-cKFEdCwBGqo.mp41.5MB

Part 03-Module 01-Lesson 04_Introduction to Kalman Filters/09. Maximize Gaussian Solution - Artificial Intelligence for Robotics-2cD8T65E-jM.mp41.52MB

Part 06-Module 01-Lesson 01_Deep Learning for Cancer Detection with Sebastian Thrun/03. Survival Rate-QPlp3NeGuSk.mp41.52MB

Part 03-Module 01-Lesson 05_Representing State and Motion/05. A Different Model-Mh0g-SMpMI4.mp41.55MB

Part 06-Module 01-Lesson 01_Deep Learning for Cancer Detection with Sebastian Thrun/01. Introduction-ZCpXvVdIdnY.mp41.55MB

Part 03-Module 01-Lesson 02_Robot Localization/17. 16 Test Sense Function V1-gytbuOI9-3g.mp41.57MB

Part 06-Module 01-Lesson 01_Deep Learning for Cancer Detection with Sebastian Thrun/14. Solution Sensitivty And Specificity-GBZjyeMjKxc.mp41.57MB

Part 06-Module 01-Lesson 01_Deep Learning for Cancer Detection with Sebastian Thrun/10. 10 Quiz Random Vs Preinitiliazed Weights V3-DRC1e4XGl2M.mp41.58MB

Part 02-Module 01-Lesson 04_ Long Short-Term Memory Networks (LSTMs)/10. Putting It All Together-IF8FlKW-Zo0.mp41.58MB

Part 09-Module 01-Lesson 01_C++ Getting Started/22. Nd113 C Basics Last Video V1-dtu-RXovl0U.mp41.63MB

Part 03-Module 01-Lesson 06_Matrices and Transformation of State/02. QUIZ Kalman Filter Prediction 01 RENDER V2-DjoBJNLzhj8.mp41.66MB

Part 08-Module 01-Lesson 01_Fully-Convolutional Neural Networks & Semantic Segmentation/06. Skip Connections-JUYLA5PWzo0.mp41.69MB

Part 02-Module 01-Lesson 04_ Long Short-Term Memory Networks (LSTMs)/16. Other Architectures-MsxFDuYlTuQ.mp41.71MB

Part 05-Module 01-Lesson 01_Feedforward and Backpropagation/04. DL 42 Neural Network Error Function (1)-SC1wEW7TtKs.mp41.72MB

Part 02-Module 01-Lesson 06_Optional Attention Mechanisms/05. 03 Attention Overview Encoding V2-IctAnMaVUKc.mp41.73MB

Part 05-Module 01-Lesson 02_Training Neural Networks/16. Error Functions Around the World-34AAcTECu2A.mp41.73MB

Part 08-Module 01-Lesson 01_Fully-Convolutional Neural Networks & Semantic Segmentation/09. Semantic Segmentation-_L5gJnZrw48.mp41.74MB

Part 03-Module 01-Lesson 04_Introduction to Kalman Filters/10. KALMAN QUIZ Shifting The Mean 01 RENDER 1 V2-gfBdoCFborg.mp41.84MB

Part 05-Module 01-Lesson 01_Feedforward and Backpropagation/03. Multiclass Classification-uNTtvxwfox0.mp41.88MB

Part 02-Module 01-Lesson 02_YOLO/09. 07 Too Many Boxes V2-nYDWsFdFnQ8.mp41.89MB

Part 03-Module 01-Lesson 02_Robot Localization/36. Sense and Move 2 - Artificial Intelligence for Robotics--wT7h9Gdm_8.mp41.93MB

Part 03-Module 01-Lesson 02_Robot Localization/25. 20 Inexact Motion 1 V3-hHAwFNsIp1c.mp41.97MB

Part 03-Module 01-Lesson 02_Robot Localization/30. Move Twice Solution - Artificial Intelligence for Robotics-oqlgQa1IdcY.mp41.99MB

Part 05-Module 01-Lesson 02_Training Neural Networks/03. Testing-EeBZpb-PSac.mp42MB

Part 03-Module 01-Lesson 05_Representing State and Motion/03. Motion Models-qSdbn_PVQnk.mp42.07MB

Part 03-Module 01-Lesson 08_Optional Vehicle Motion and Calculus/24. Trigonometry And Vehicle Motion-WY3T-9GHI_0.mp42.09MB

Part 03-Module 01-Lesson 02_Robot Localization/26. Inexact Move Function - Artificial Intelligence for Robotics-68Kao9dkIKA.mp42.11MB

Part 03-Module 01-Lesson 01_Introduction to Motion/04. Optical Flow-TOS8UJwCtTg.mp42.13MB

Part 03-Module 01-Lesson 04_Introduction to Kalman Filters/14. KALMAN QUIZ Parameter Update 01 RENDER V3-UUXETqShme4.mp42.14MB

Part 01-Module 01-Lesson 06_CNN Layers and Feature Visualization/16. 动量-r-rYz_PEWC8.mp42.14MB

Part 05-Module 01-Lesson 02_Training Neural Networks/15. Momentum-r-rYz_PEWC8.mp42.14MB

Part 03-Module 01-Lesson 03_Mini-project 2D Histogram Filter/01. Project Overview-uaWZNKGTtgM.mp42.17MB

Part 06-Module 01-Lesson 01_Deep Learning for Cancer Detection with Sebastian Thrun/04. Medical Classification-RCOSP60dV7U.mp42.2MB

Part 09-Module 01-Lesson 01_C++ Getting Started/17. Function Signatures 3 V1-U3QAFb3AS1M.mp42.2MB

Part 02-Module 01-Lesson 05_Hyperparameters/02. Introduction-erwnzFD7AeE.mp42.22MB

Part 02-Module 01-Lesson 04_ Long Short-Term Memory Networks (LSTMs)/06. Learn Gate-aVHVI7ovbHY.mp42.22MB

Part 03-Module 01-Lesson 02_Robot Localization/08. 09 Probability After Sense V1-aWQMJQQmNGw.mp42.23MB

Part 02-Module 01-Lesson 04_ Long Short-Term Memory Networks (LSTMs)/14. Sequence Batching-pdSr5F-9qE0.mp42.29MB

Part 05-Module 01-Lesson 02_Training Neural Networks/12. Other Activation Functions-kA-1vUt6cvQ.mp42.3MB

Part 09-Module 02-Lesson 02_C++ Optimization Practice/19. Nd113 C L2 01 V1-h_P7ceb5ido.mp42.31MB

Part 06-Module 01-Lesson 01_Deep Learning for Cancer Detection with Sebastian Thrun/17. 16 Solution Diagnosing Cancer V3-IJYvt2ssUFk.mp42.31MB

Part 03-Module 01-Lesson 02_Robot Localization/14. Normalized Sense Function - Artificial Intelligence for Robotics-GqWszyHTYas.mp42.34MB

Part 03-Module 01-Lesson 02_Robot Localization/30. Move Twice - Artificial Intelligence for Robotics-sKiumVTdpgY.mp42.37MB

Part 02-Module 01-Lesson 06_Optional Attention Mechanisms/08. 05 Attention Encoder V2-sphe9LDT4rA.mp42.41MB

Part 06-Module 01-Lesson 01_Deep Learning for Cancer Detection with Sebastian Thrun/22. Visualization-aGIGB4Ta3_A.mp42.43MB

Part 03-Module 01-Lesson 07_Simultaneous Localization and Mapping/04. 04 Implementing Constraints Quiz V1-2V3ZF08TcX8.mp42.46MB

Part 02-Module 01-Lesson 06_Optional Attention Mechanisms/02. Applications seq2seq-tDJBDwriJYQ.mp42.48MB

Part 01-Module 01-Lesson 05_Feature Vectors/02. Feature Vectors--PF1_MITrOw.mp42.5MB

Part 03-Module 01-Lesson 02_Robot Localization/05. 03 Localization V1-OB6GZxfvESw.mp42.52MB

Part 08-Module 01-Lesson 01_Fully-Convolutional Neural Networks & Semantic Segmentation/11. Scene Understanding-aMQREc-mP50.mp42.52MB

Part 03-Module 01-Lesson 04_Introduction to Kalman Filters/26. KALMAN QUIZ Kalman Prediction V1-d8Gx4-RghD0.mp42.53MB

Part 03-Module 01-Lesson 02_Robot Localization/04. 概率分布入门 1-gqPjMDVFvNg.mp42.55MB

Part 02-Module 01-Lesson 07_Image Captioning/02. 02 Leveraging Neural Networks V3-thClOUTiNxY.mp42.56MB

Part 08-Module 01-Lesson 01_Fully-Convolutional Neural Networks & Semantic Segmentation/02. Why Fully Convolutional Networks (FCNs) -WQ_YOz1o9GM.mp42.57MB

Part 02-Module 01-Lesson 07_Image Captioning/10. 08 Video Captioning V1-I_m9JyKTfbQ.mp42.61MB

Part 03-Module 01-Lesson 01_Introduction to Motion/02. Localization V1 (1)-QkVyEMTUkAw.mp42.62MB

Part 06-Module 01-Lesson 01_Deep Learning for Cancer Detection with Sebastian Thrun/21. ROC Curve-fWwe_JlpnlQ.mp42.68MB

Part 03-Module 01-Lesson 04_Introduction to Kalman Filters/05. KALMAN Gaussian Intro RENDER 1 1 V3-S2v1CExswT4.mp42.71MB

Part 01-Module 01-Lesson 02_Image Representation & Classification/03. 08. Computer Vision Pipeline-64hFcqhnNow.mp42.79MB

Part 05-Module 01-Lesson 01_Feedforward and Backpropagation/03. 29 Neural Network Architecture 2-FWN3Sw5fFoM.mp42.83MB

Part 06-Module 01-Lesson 01_Deep Learning for Cancer Detection with Sebastian Thrun/11. Solution Random Vs Preinitialized Thoughts-sOuoRZRKDzs.mp42.83MB

Part 01-Module 01-Lesson 06_CNN Layers and Feature Visualization/20. 05 Feature Maps V1RENDER V3-oRhsJHHWtu8.mp42.84MB

Part 06-Module 01-Lesson 01_Deep Learning for Cancer Detection with Sebastian Thrun/05. The Data-2RLbbV7MQNA.mp42.85MB

Part 03-Module 01-Lesson 05_Representing State and Motion/08. Lesson Outline-jh7wLGXrm3E.mp42.86MB

Part 02-Module 01-Lesson 04_ Long Short-Term Memory Networks (LSTMs)/13. Character-Wise RNN-m_S2hs6-j5w.mp42.88MB

Part 02-Module 01-Lesson 02_YOLO/06. 05 Training On A Grid V2-uhefpakvXh8.mp42.89MB

Part 01-Module 01-Lesson 05_Feature Vectors/04. 02 Introduction To ORB V3-WN37zcMhMas.mp42.91MB

Part 05-Module 01-Lesson 02_Training Neural Networks/02. Training Optimization-UiGKhx9pUYc.mp42.96MB

Part 02-Module 01-Lesson 01_Advanced CNN Architectures/09. 08 Faster RCNN V1 RENDER V2-ySh_Q3KTTBY.mp42.99MB

Part 02-Module 01-Lesson 01_Advanced CNN Architectures/08. 07 Fast RCNN V1 RENDER V2-6FOBZ9OgWlY.mp43MB

Part 08-Module 01-Lesson 01_Fully-Convolutional Neural Networks & Semantic Segmentation/03. Fully Convolutional Networks-_Lh2ozg5yTs.mp43MB

Part 03-Module 01-Lesson 07_Simultaneous Localization and Mapping/19. 17 Confident Measurements QUIZ RENDER V2-WRANOBm89I4.mp43.03MB

Part 03-Module 01-Lesson 04_Introduction to Kalman Filters/18. KALMAN QUIZ Gaussian Motion 01 RENDER V2-LFPT0R3VaPs.mp43.04MB

Part 01-Module 01-Lesson 03_Convolutional Filters and Edge Detection/23. Haar Cascades-vALIpxVfKRc.mp43.05MB

Part 06-Module 01-Lesson 01_Deep Learning for Cancer Detection with Sebastian Thrun/25. Confusion Matrix-3rpN-YYlfes.mp43.07MB

Part 02-Module 01-Lesson 01_Advanced CNN Architectures/02. 02 More Than Classification RENDER V2-vBE5KvvAYzg.mp43.08MB

Part 05-Module 01-Lesson 01_Feedforward and Backpropagation/03. Layers-pg99FkXYK0M.mp43.11MB

Part 02-Module 01-Lesson 06_Optional Attention Mechanisms/09. 06 Attention Decoder V1-5mMz6nN9_Ss.mp43.15MB

Part 02-Module 01-Lesson 06_Optional Attention Mechanisms/06. 04 Attention Overview Decoding V2-DJxiPd585GY.mp43.2MB

Part 03-Module 01-Lesson 08_Optional Vehicle Motion and Calculus/13. 06 L Reasoning About Two Peaks H1 V1-bgPS1GO1EJs.mp43.2MB

Part 03-Module 01-Lesson 05_Representing State and Motion/20. State Transformation Matrix-DRRuQMYo800.mp43.21MB

Part 03-Module 01-Lesson 07_Simultaneous Localization and Mapping/18. 16 Introducing Noise Solution RENDER V1-X5kh82oke5w.mp43.21MB

Part 02-Module 01-Lesson 07_Image Captioning/08. Tokenization-4Ieotbeh4u8.mp43.22MB

Part 09-Module 02-Lesson 01_C++ Intro to Optimization/01. Course Introduction-Lwc5oYApdUM.mp43.25MB

Part 08-Module 01-Lesson 01_Fully-Convolutional Neural Networks & Semantic Segmentation/15. Outro-vyNI5hdMigs.mp43.25MB

Part 01-Module 01-Lesson 03_Convolutional Filters and Edge Detection/18. Hough Transform-RIOzsF1_xuo.mp43.25MB

Part 03-Module 01-Lesson 05_Representing State and Motion/24. Working With Matrices-nruxu8pr6i8.mp43.27MB

Part 03-Module 01-Lesson 06_Matrices and Transformation of State/01. Kalman Filter Land RENDER 1 V1-6xupqulu0bc.mp43.27MB

Part 03-Module 01-Lesson 02_Robot Localization/33. 27 Sense And Move V2-v2dYzm6-YVs.mp43.28MB

Part 05-Module 01-Lesson 01_Feedforward and Backpropagation/05. Calculating The Gradient 1 -tVuZDbUrzzI.mp43.31MB

Part 05-Module 01-Lesson 03_Deep Learning with PyTorch/06. PyTorch - Part 4-AEJV_RKZ7VU.mp43.32MB

Part 01-Module 01-Lesson 04_Types of Features & Image Segmentation/01. Types Of Features-cJHro29nzgg.mp43.33MB

Part 01-Module 01-Lesson 06_CNN Layers and Feature Visualization/23. 10 Visualizing Activations V1 RENDER V2-CJLNTOXqt3I.mp43.35MB

Part 08-Module 01-Lesson 01_Fully-Convolutional Neural Networks & Semantic Segmentation/12. IoU---9BTjOsO6U.mp43.36MB

Part 02-Module 01-Lesson 05_Hyperparameters/07. Number Of Hidden Units Layers-IkGAIQH5wH8.mp43.4MB

Part 06-Module 01-Lesson 01_Deep Learning for Cancer Detection with Sebastian Thrun/23. What Is The Neural Network Looking At-qN-rvoxPbBw.mp43.46MB

Part 03-Module 01-Lesson 02_Robot Localization/17. Test Sense Function Solution - Artificial Intelligence for Robotics-F8AHaaJVmkw.mp43.47MB

Part 01-Module 01-Lesson 06_CNN Layers and Feature Visualization/28. 20 Summary Of Feature Viz V2 RENDER V2-r2LBoEkXskU.mp43.49MB

Part 03-Module 01-Lesson 06_Matrices and Transformation of State/06. KALMAN Kalman Filter Design RENDER V2-7C_tsAr8PNM.mp43.57MB

Part 02-Module 01-Lesson 04_ Long Short-Term Memory Networks (LSTMs)/02. RNN Vs LSTM-70MgF-IwAr8.mp43.58MB

Part 09-Module 02-Lesson 01_C++ Intro to Optimization/10. 04 L C And RAM V1 RENDER V1-60jEbKV1UOI.mp43.58MB

Part 03-Module 01-Lesson 01_Introduction to Motion/05. 01 Motion Vector V2-I3f3IEUI2tg.mp43.64MB

Part 03-Module 01-Lesson 05_Representing State and Motion/09. Always Moving-EQBQlHvxAQA.mp43.65MB

Part 03-Module 01-Lesson 01_Introduction to Motion/08. 04 Tracking Features V2-uFf6IZ5MxgU.mp43.74MB

Part 03-Module 01-Lesson 06_Matrices and Transformation of State/31. Nd113 Matrices L3 12 V1-BRLmFGScL_k.mp43.75MB

Part 03-Module 01-Lesson 08_Optional Vehicle Motion and Calculus/11. Nd113 C6 L2 03 L Acceleration Basics V2-ea6b4PZ7YXU.mp43.76MB

Part 02-Module 01-Lesson 06_Optional Attention Mechanisms/04. 02 Sequence To Sequence Recap V2-MRPHIPR0pGE.mp43.76MB

Part 03-Module 01-Lesson 06_Matrices and Transformation of State/09. Nd113 C2 L3 09 L Simplifying The Kalman Filter Equations V3-UpC0D-SEtD0.mp43.8MB

Part 02-Module 01-Lesson 07_Image Captioning/11. 09 On To The Project V2-MsxNRaYTNSk.mp43.87MB

Part 01-Module 01-Lesson 02_Image Representation & Classification/01. 01 Pattern Recognition V1-cX5EE1WEqhY.mp43.87MB

Part 02-Module 01-Lesson 01_Advanced CNN Architectures/10. 09 Detection Without Proposals Summary V1-IMnt1HFu_nc.mp43.88MB

Part 02-Module 01-Lesson 02_YOLO/10. 08 Intersection Over Union IOU V1-ieKEHlEjIsY.mp43.89MB

Part 05-Module 01-Lesson 02_Training Neural Networks/13. Batch vs Stochastic Gradient Descent-2p58rVgqsgo.mp43.95MB

Part 02-Module 01-Lesson 04_ Long Short-Term Memory Networks (LSTMs)/03. LSTM Basics-gjb68a4XsqE.mp44.03MB

Part 01-Module 01-Lesson 01_Welcome to Computer Vision/01. 1 HS Welcome To Computer Vision V2Demo1 V2-9s-gm2ZvODI.mp44.05MB

Part 03-Module 01-Lesson 05_Representing State and Motion/01. Localization Steps-4SiMoSTf4rQ.mp44.06MB

Part 07-Module 01-Lesson 01_Sentiment Analysis/01. Introducing Andrew Trask-ltO71Bm8b3M.mp44.08MB

Part 03-Module 01-Lesson 02_Robot Localization/18. Multiple Measurements - Artificial Intelligence for Robotics-gDO4sF8gR9k.mp44.1MB

Part 03-Module 01-Lesson 01_Introduction to Motion/06. 02 Brightness Constancy Assumption V3-GHz9Yzt5tro.mp44.1MB

Part 02-Module 01-Lesson 05_Hyperparameters/08. RNN Hyperparameters-yQvnv7l_aUo.mp44.12MB

Part 03-Module 01-Lesson 04_Introduction to Kalman Filters/01. 矩阵介绍-Ugx3mldc0lE.mp44.15MB

Part 02-Module 01-Lesson 06_Optional Attention Mechanisms/13. 09 Additive Attention V2-93VfVWZ-IvY.mp44.17MB

Part 01-Module 01-Lesson 01_Welcome to Computer Vision/02. 2 HSA Computer Vision In Industry V3 Demo02 V3-_8be3GdqfqU.mp44.17MB

Part 03-Module 01-Lesson 07_Simultaneous Localization and Mapping/01. 02 SLAM V1-UVkkDPJshgM.mp44.18MB

Part 01-Module 01-Lesson 06_CNN Layers and Feature Visualization/16. Dropout-Ty6K6YiGdBs.mp44.22MB

Part 05-Module 01-Lesson 02_Training Neural Networks/08. Dropout-Ty6K6YiGdBs.mp44.22MB

Part 09-Module 02-Lesson 01_C++ Intro to Optimization/03. 02 L Intro To Comp HW V1 RENDER V1-WDMGkq9mkB8.mp44.26MB

Part 09-Module 01-Lesson 04_C++ Object Oriented Programming/01. Introduction-4xHI5LFX-cQ.mp44.28MB

Part 03-Module 01-Lesson 02_Robot Localization/16. Normalized Sense Function Solution - Artificial Intelligence for Robotics-UX3W8TUKbJ0.mp44.29MB

Part 03-Module 01-Lesson 02_Robot Localization/36. Sense And Move 2 Solution Director'SCut-7gl2GF-laOQ.mp44.32MB

Part 01-Module 01-Lesson 01_Welcome to Computer Vision/06. 4 HSA Learning In The Classroom V3 Demov1 V3-KN_SROb6SnM.mp44.32MB

Part 02-Module 01-Lesson 07_Image Captioning/05. 04 CNNRNN Model V3-n7kdMiX1Xz8.mp44.39MB

Part 03-Module 01-Lesson 02_Robot Localization/02. Reduzindo a incerteza-zuFMhmKQ--o.mp44.4MB

Part 01-Module 01-Lesson 02_Image Representation & Classification/07. Image Formation-6ZVnQYzfpis.mp44.42MB

Part 03-Module 01-Lesson 08_Optional Vehicle Motion and Calculus/05. Nd113 C6 L1 14 L A Typical Calculus Problem Part2 V2-0ww_q51P8uY.mp44.45MB

Part 08-Module 01-Lesson 01_Fully-Convolutional Neural Networks & Semantic Segmentation/01. Intro-1sm1EbfilXI.mp44.45MB

Part 09-Module 02-Lesson 01_C++ Intro to Optimization/12. C Opt 05 L V3-rTtZVyWxYG8.mp44.47MB

Part 02-Module 01-Lesson 06_Optional Attention Mechanisms/02. Architecture encoder decoder-dkHdEAJnV_w.mp44.49MB

Part 01-Module 01-Lesson 03_Convolutional Filters and Edge Detection/20. Hough Line Detection-PVIUkQKbrUw.mp44.5MB

Part 01-Module 01-Lesson 06_CNN Layers and Feature Visualization/19. 04 Feature Visualization V1 RENDER V2-xwGa7RFg1EQ.mp44.54MB

Part 03-Module 01-Lesson 06_Matrices and Transformation of State/04. More Kalman Filters RENDER V2-5QYGm4D9z6Y.mp44.55MB

Part 01-Module 01-Lesson 01_Welcome to Computer Vision/03. 3 HSA Course Outline V3 Demo01 1 V3-INMNyJGB2DI.mp44.56MB

Part 01-Module 01-Lesson 05_Feature Vectors/13. Histogram of Oriented Gradients-dqe9zGtxoNM.mp44.56MB

Part 01-Module 01-Lesson 06_CNN Layers and Feature Visualization/01. 02 Intro To CNN Layers V1 RENDER V3-hT6zBYCuAfw.mp44.66MB

Part 06-Module 01-Lesson 01_Deep Learning for Cancer Detection with Sebastian Thrun/02. 02 Skin Cancer V4-70jGZeiTNgk.mp44.73MB

Part 05-Module 01-Lesson 01_Feedforward and Backpropagation/03. Combinando modelos-Boy3zHVrWB4.mp44.73MB

Part 03-Module 01-Lesson 04_Introduction to Kalman Filters/03. KALMAN Tracking Intro RENDER V2-C73G7vfVNQc.mp44.74MB

Part 03-Module 01-Lesson 07_Simultaneous Localization and Mapping/12. 12 Omega And Xi QUIZ RENDER V1-KqCBoAaa5jQ.mp44.75MB

Part 02-Module 01-Lesson 05_Hyperparameters/05. Minibatch Size-GrrO1NFxaW8.mp44.78MB

Part 02-Module 01-Lesson 02_YOLO/05. 04 Using A Grid To Improve Localization V2-OmgR35Go79Y.mp44.85MB

Part 05-Module 01-Lesson 02_Training Neural Networks/05. Model Complexity Graph-NnS0FJyVcDQ.mp44.9MB

Part 03-Module 01-Lesson 05_Representing State and Motion/07. Quantifying State-9zMbwSqTZAc.mp45.01MB

Part 01-Module 01-Lesson 06_CNN Layers and Feature Visualization/03. 03 Data And Lesson Outline RENDER V2-jPr-5aZA6NE.mp45.03MB

Part 06-Module 01-Lesson 01_Deep Learning for Cancer Detection with Sebastian Thrun/24. Confusion Matrix-Question 1-9GLNjmMUB_4.mp45.04MB

Part 03-Module 01-Lesson 01_Introduction to Motion/03. Motion -A-QJf04LBb0.mp45.05MB

Part 03-Module 01-Lesson 05_Representing State and Motion/10. Car Object-SnfhGZ76h7Y.mp45.12MB

Part 03-Module 01-Lesson 05_Representing State and Motion/19. State Vector-st26ov_TVwM.mp45.12MB

Part 09-Module 01-Lesson 01_C++ Getting Started/10. Doubles Are Bigger-uhwTWgmM2iY.mp45.13MB

Part 01-Module 01-Lesson 03_Convolutional Filters and Edge Detection/10. Low-pass Filters-jy5Be9vf2rk.mp45.19MB

Part 03-Module 01-Lesson 02_Robot Localization/03. Usando dados do sensor-vhl-SADfti8.mp45.21MB

Part 01-Module 01-Lesson 04_Types of Features & Image Segmentation/06. Image Contours-Wcbrl7Wr_kU.mp45.27MB

Part 05-Module 01-Lesson 01_Feedforward and Backpropagation/04. DL 41 Feedforward FIX V2-hVCuvMGOfyY.mp45.33MB

Part 03-Module 01-Lesson 08_Optional Vehicle Motion and Calculus/14. 07 L The Integral Area Under A Curve H1 V2-QNvgwoIrsIE.mp45.34MB

Part 09-Module 02-Lesson 01_C++ Intro to Optimization/07. 03 L Binary V1 RENDER V1-K6CpHxnhc2s.mp45.37MB

Part 03-Module 01-Lesson 02_Robot Localization/06. 05 Total Probability V4-RCEieE2t8U4.mp45.46MB

Part 01-Module 01-Lesson 03_Convolutional Filters and Edge Detection/11. Gaussian Blur-1tlPonqIOrU.mp45.51MB

Part 06-Module 01-Lesson 01_Deep Learning for Cancer Detection with Sebastian Thrun/12. Validating The Training-Oxm9ofvov3I.mp45.51MB

Part 03-Module 01-Lesson 07_Simultaneous Localization and Mapping/02. 03 Graph SLAM Quiz V2-OGBC9HrVqd4.mp45.54MB

Part 02-Module 01-Lesson 07_Image Captioning/03. 03 Captions And The COCO Dataset V3-DMmJs1w1n7A.mp45.61MB

Part 03-Module 01-Lesson 08_Optional Vehicle Motion and Calculus/14. Nd113 C6 07 L The Integral Area Under A Curve H1 V2-Nhpvh2dolcE.mp45.69MB

Part 05-Module 01-Lesson 01_Feedforward and Backpropagation/05. DL 46 Calculating The Gradient 2 V2 (2)-7lidiTGIlN4.mp45.69MB

Part 03-Module 01-Lesson 08_Optional Vehicle Motion and Calculus/28. Conclusion-gMbDqd4ItiU.mp45.72MB

Part 01-Module 01-Lesson 06_CNN Layers and Feature Visualization/09. Pooling Layers-OkkIZNs7Cyc.mp45.82MB

Part 02-Module 01-Lesson 01_Advanced CNN Architectures/07. 06 RCNN V1 RENDER V2-EchapZJMTYU.mp45.84MB

Part 02-Module 01-Lesson 06_Optional Attention Mechanisms/16. 11 Other Attention Methods V2-VmsR9FVpQiM.mp45.84MB

Part 09-Module 01-Lesson 01_C++ Getting Started/02. Nd113 C3 L1 04 L Lesson Overview 2 V1-DjT2E23xhj8.mp45.85MB

Part 02-Module 01-Lesson 07_Image Captioning/01. 01 L Introduction V3-dobNslC2y-o.mp45.94MB

Part 03-Module 01-Lesson 08_Optional Vehicle Motion and Calculus/25. Solving Trig Problems Part1-qI4i845d7Qg.mp45.97MB

Part 02-Module 01-Lesson 02_YOLO/01. 01 Introduction V3-uyefSrHZesY.mp45.97MB

Part 02-Module 01-Lesson 07_Image Captioning/06. 05 The Glue V5-u2ZdcUDnHm0.mp46.02MB

Part 09-Module 01-Lesson 01_C++ Getting Started/01. Introduction-ahoiVrq4qAk.mp46.03MB

Part 01-Module 01-Lesson 04_Types of Features & Image Segmentation/09. K-means Clustering-Cf_LSDCEBzk.mp46.06MB

Part 03-Module 01-Lesson 05_Representing State and Motion/14. Nd113 C2 L3 20 L Adding Color V2-iltQBIpbCSw.mp46.06MB

Part 02-Module 01-Lesson 02_YOLO/02. 02 YOLO Output V2-MyOuuwk0qC4.mp46.07MB

Part 09-Module 01-Lesson 01_C++ Getting Started/15. Two Functions Same Name-0ZF649G58l4.mp46.09MB

Part 02-Module 01-Lesson 06_Optional Attention Mechanisms/17. 12 The Transformer And Self Attention V2-F-XN72bQiMQ.mp46.1MB

Part 03-Module 01-Lesson 01_Introduction to Motion/01. Object Tracking V4 (1)-ciEo6PyMTeM.mp46.11MB

Part 03-Module 01-Lesson 02_Robot Localization/20. Multiple Measurements Solution - Artificial Intelligence for Robotics--3qTapGGa-8.mp46.21MB

Part 01-Module 01-Lesson 04_Types of Features & Image Segmentation/10. K-means Implementation-poKlg-aB4rU.mp46.26MB

Part 03-Module 01-Lesson 04_Introduction to Kalman Filters/17. New Mean and Variance Solution - Artificial Intelligence for Robotics-SwxRWZaC1FM.mp46.31MB

Part 05-Module 01-Lesson 02_Training Neural Networks/04. Underfitting And Overfitting-xj4PlXMsN-Y.mp46.42MB

Part 02-Module 01-Lesson 02_YOLO/14. 11 YOLO Algorithm V3-ZbQzCHQ8YEo.mp46.52MB

Part 05-Module 01-Lesson 01_Feedforward and Backpropagation/05. Backpropagation V2-1SmY3TZTyUk.mp46.52MB

Part 01-Module 01-Lesson 02_Image Representation & Classification/28. Nd113 C7 45 L Classification V1-LWD1M2vqXXo.mp46.54MB

Part 02-Module 01-Lesson 02_YOLO/07. 06 Generating Bounding Boxes V3-TGfPX-XcyOs.mp46.55MB

Part 02-Module 01-Lesson 02_YOLO/12. 09 NonMaximal Suppression V1-TE6M29Jo9hk.mp46.6MB

Part 02-Module 01-Lesson 06_Optional Attention Mechanisms/15. 10 Computer Vision Applications V3-bhWwc4BYTYc.mp46.62MB

Part 01-Module 01-Lesson 03_Convolutional Filters and Edge Detection/07. Creating a Filter-VEsdTRBH3D8.mp46.63MB

Part 07-Module 01-Lesson 01_Sentiment Analysis/08. Transforming Text into Numbers-7rHBU5cbePE.mp46.64MB

Part 02-Module 01-Lesson 06_Optional Attention Mechanisms/11. 07 Additive And Multiplicative Attention V1-2eqIUDjefNg.mp46.66MB

Part 06-Module 01-Lesson 01_Deep Learning for Cancer Detection with Sebastian Thrun/18. ROC Curve-2Iw5TiGzJI4.mp46.66MB

Part 02-Module 01-Lesson 01_Advanced CNN Architectures/06. 05 Region Proposals V1 RENDER V2-HLwpr7h3rPY.mp46.75MB

Part 03-Module 01-Lesson 08_Optional Vehicle Motion and Calculus/18. Rate Gyros-TmnecSf80b0.mp46.82MB

Part 03-Module 01-Lesson 02_Robot Localization/04. 概率分布入门 2-PglBg4eb_5M.mp46.85MB

Part 03-Module 01-Lesson 08_Optional Vehicle Motion and Calculus/04. Nd113 C6 L1 09 L Interpreting Position Vs Time Graphs V3-NAEasXHN_PU.mp46.95MB

Part 01-Module 01-Lesson 03_Convolutional Filters and Edge Detection/15. Canny Edge Detection-Nm1H2xMMS3I.mp46.96MB

Part 01-Module 01-Lesson 05_Feature Vectors/03. 01 Realtime Feature Detection V2-zPxylrXf-Gs.mp46.97MB

Part 01-Module 01-Lesson 05_Feature Vectors/05. 03 Fast V3-DCHAc6fjcVM.mp47.25MB

Part 02-Module 01-Lesson 03_RNN's/24. RNN Summary-nXP0oGGRrO8.mp47.26MB

Part 03-Module 01-Lesson 02_Robot Localization/13. Sense Function Solution - Artificial Intelligence for Robotics-Y5iFxWRTw1c.mp47.39MB

Part 09-Module 01-Lesson 01_C++ Getting Started/02. Lesson Overview C++-lR3PH3bL-9U.mp47.4MB

Part 03-Module 01-Lesson 02_Robot Localization/38. Lesson Overview C++-lR3PH3bL-9U.mp47.4MB

Part 03-Module 01-Lesson 02_Robot Localization/28. Inexact Move Function Solution - Artificial Intelligence for Robotics-QCnPJcNprEU.mp47.42MB

Part 03-Module 01-Lesson 06_Matrices and Transformation of State/08. Nd113 C2 L3 08 L The Kalman Filter Equations V2-X9UUpk5URuw.mp47.49MB

Part 01-Module 01-Lesson 02_Image Representation & Classification/13. Color Thresholds-08ZlYZJaiUg.mp47.54MB

Part 05-Module 01-Lesson 02_Training Neural Networks/07. Regularization-ndYnUrx8xvs.mp47.57MB

Part 02-Module 01-Lesson 07_Image Captioning/09. 07 RNN Training V4-P-tHxD7kRmA.mp47.58MB

Part 03-Module 01-Lesson 08_Optional Vehicle Motion and Calculus/20. Working with Real Data-WvEcWtAz-OQ.mp47.66MB

Part 09-Module 02-Lesson 01_C++ Intro to Optimization/02. C Opt 01 L V2-Kdx1_BI5ddc.mp47.76MB

Part 01-Module 01-Lesson 03_Convolutional Filters and Edge Detection/01. Nd113 C7 36 L Filters And Finding Edges V1-f3H2EtiZLOQ.mp47.91MB

Part 01-Module 01-Lesson 05_Feature Vectors/07. 04 Brief V4-EKIPEPpRciw.mp47.91MB

Part 09-Module 01-Lesson 03_Practical C++/01. Introduction To Compilation-dyzGEB8YDGg.mp47.96MB

Part 01-Module 01-Lesson 02_Image Representation & Classification/04. 09. Training a Model-m4GVfwVkj74.mp48.01MB

Part 02-Module 01-Lesson 06_Optional Attention Mechanisms/12. 08 Multiplicative Attention V2-1-OwCgrx1eQ.mp48.01MB

Part 09-Module 01-Lesson 01_C++ Getting Started/17. Function Signatures 2-Sx4AWTmXl2U.mp48.1MB

Part 02-Module 01-Lesson 01_Advanced CNN Architectures/03. 03 Classification And Localization RENDER V3-UqNg9d6cKQU.mp48.12MB

Part 06-Module 01-Lesson 01_Deep Learning for Cancer Detection with Sebastian Thrun/26. Conclusion-WhpE_8sTt-0.mp48.2MB

Part 01-Module 01-Lesson 03_Convolutional Filters and Edge Detection/05. High-pass Filters-OpcFn_H2V-Q.mp48.25MB

Part 03-Module 01-Lesson 04_Introduction to Kalman Filters/09. Maximize Gaussian - Artificial Intelligence for Robotics-fRYtUP0P4Lg.mp48.34MB

Part 01-Module 01-Lesson 05_Feature Vectors/10. 07 Feature Matching V2-RH05Wnl1-2A.mp48.35MB

Part 02-Module 01-Lesson 01_Advanced CNN Architectures/01. 01 CNNs And Scene Understanding RENDER Full V2-_iRqSOsTBQU.mp48.43MB

Part 02-Module 01-Lesson 01_Advanced CNN Architectures/04. 04 Bounding Boxes And Regression V1 RENDER V3-2YM82c7SaCo.mp48.54MB

Part 03-Module 01-Lesson 08_Optional Vehicle Motion and Calculus/15. Approximating The Integral-9C05AHzI_I8.mp48.57MB

Part 03-Module 01-Lesson 02_Robot Localization/22. Move Function - Artificial Intelligence for Robotics-wfjE0mVADIk.mp48.7MB

Part 07-Module 01-Lesson 01_Sentiment Analysis/10. Mini Project 2 Solution-45ihpPaeO8E.mp49.22MB

Part 02-Module 01-Lesson 02_YOLO/03. 03 A Convolutional Approach To Sliding Windows V3-8qYqqibIz90.mp49.42MB

Part 01-Module 01-Lesson 06_CNN Layers and Feature Visualization/21. 06 First Convolutional Layer T1 V1 RENDER V2-hIHDMWVSfsM.mp49.51MB

Part 01-Module 01-Lesson 04_Types of Features & Image Segmentation/02. Corner Detectors-jemzDq07MEI.mp49.51MB

Part 01-Module 01-Lesson 02_Image Representation & Classification/10. Color Images--XbXiiGQ9gw.mp49.6MB

Part 02-Module 01-Lesson 05_Hyperparameters/03. Learning Rate-HLMjeDez7ps.mp49.62MB

Part 03-Module 01-Lesson 02_Robot Localization/35. Sense and Move Solution - Artificial Intelligence for Robotics-1s2dRczcu1A.mp49.74MB

Part 01-Module 01-Lesson 05_Feature Vectors/11. 08 ORB In Video V2 (1)-Vzs6B1dFQC0.mp49.77MB

Part 02-Module 01-Lesson 07_Image Captioning/07. 06 Tokenizing Captions V3-aeEFb0eSzJ8.mp49.89MB

Part 01-Module 01-Lesson 02_Image Representation & Classification/17. Color Spaces and Transforms-B350aJVSsFc.mp49.9MB

Part 01-Module 01-Lesson 02_Image Representation & Classification/23. Nd113 C7 29 L Features-HshygbfQylA.mp410.05MB

Part 07-Module 01-Lesson 01_Sentiment Analysis/11. Building a Neural Network-aM2k7RTjjJI.mp410.17MB

Part 02-Module 01-Lesson 03_RNN's/12. 14 RNN A V4 Final-ofbnDxGSUcg.mp410.43MB

Part 09-Module 01-Lesson 01_C++ Getting Started/06. Static Vs Dynamic Typing-D7v6iIAORkE.mp410.49MB

Part 02-Module 01-Lesson 03_RNN's/14. 17 RNN Unfolded V3 Final-xLIA_PTWXog.mp410.5MB

Part 09-Module 01-Lesson 04_C++ Object Oriented Programming/03. Why Use Object Oriented Programming-G2KzZfNu9Ak.mp410.64MB

Part 03-Module 01-Lesson 04_Introduction to Kalman Filters/02. Introduction-XZL934YQ-FQ.mp410.68MB

Part 01-Module 01-Lesson 02_Image Representation & Classification/02. 05. Emotional Intelligence-D_LzJsJH5qk.mp410.88MB

Part 01-Module 01-Lesson 05_Feature Vectors/08. 05 Scale And RotationInvariance V2-2k3T6rfjvx0.mp410.92MB

Part 03-Module 01-Lesson 02_Robot Localization/24. Move Function Solution - Artificial Intelligence for Robotics-TnFq6hufsYs.mp410.96MB

Part 01-Module 01-Lesson 02_Image Representation & Classification/14. Coding A Blue Screen-jeeDryFxodk.mp411.4MB

Part 09-Module 01-Lesson 01_C++ Getting Started/16. Function Signatures 1-T6kQ_4w98IQ.mp411.65MB

Part 07-Module 01-Lesson 01_Sentiment Analysis/23. Andrew Trask - Outro-nIF0GLOQglQ.mp411.79MB

Part 09-Module 01-Lesson 01_C++ Getting Started/04. Why C++-_t4ZvwfnuCA.mp411.98MB

Part 02-Module 01-Lesson 06_Optional Attention Mechanisms/01. 01 Introduction To Attention V2-NCn97L5WbCY.mp412MB

Part 02-Module 01-Lesson 02_YOLO/13. 10 Anchor Boxes V3-IzILYgVb76g.mp412.15MB

Part 09-Module 02-Lesson 02_C++ Optimization Practice/16. Nd113 Story 1 V1-lIe2zso8A-w.mp412.76MB

Part 02-Module 01-Lesson 03_RNN's/08. 13 Overfitting Intro V4 Final-rmBLnVbFfFY.mp412.76MB

Part 03-Module 01-Lesson 02_Robot Localization/11. Sense Function - Artificial Intelligence for Robotics-eIjyrQpDogg.mp412.91MB

Part 03-Module 01-Lesson 08_Optional Vehicle Motion and Calculus/01. 惯性导航-vWgG0d2HOVE.mp412.92MB

Part 09-Module 01-Lesson 01_C++ Getting Started/15. Two Functions Same Name-9SgmzOfBmRU.mp413.16MB

Part 03-Module 01-Lesson 04_Introduction to Kalman Filters/23. Kalman Filter Code - Artificial Intelligence for Robotics-3xBycKfnCOQ.mp413.28MB

Part 03-Module 01-Lesson 07_Simultaneous Localization and Mapping/21. 18 Implementing SLAM QUIZ RENDER V1-Ptx33qEaUQQ.mp413.61MB

Part 05-Module 01-Lesson 03_Deep Learning with PyTorch/03. Part 1 V2-n4mbZYIfKb4.mp413.81MB

Part 01-Module 01-Lesson 02_Image Representation & Classification/06. AffdexMe Demo-dpFtXDqakvY.mp413.96MB

Part 05-Module 01-Lesson 03_Deep Learning with PyTorch/09. PyTorch - Part 7-hFu7GTfRWks.mp414.62MB

Part 01-Module 01-Lesson 02_Image Representation & Classification/21. Labeled Data and Accuracy-FN96OM_JGyM.mp414.66MB

Part 02-Module 01-Lesson 03_RNN's/09. 10 Backpropagation Example A V3 Final-3k72z_WaeXg.mp414.77MB

Part 05-Module 01-Lesson 03_Deep Learning with PyTorch/08. Py Part 6 V1-HiTih59dCWQ.mp415.94MB

Part 02-Module 01-Lesson 03_RNN's/19. 21 RNN BPTT C V7 Final-uBy_eIJDD1M.mp417.23MB

Part 02-Module 01-Lesson 03_RNN's/04. 03 RNN Applications V3 Final-6JbTNARuKII.mp417.27MB

Part 07-Module 01-Lesson 01_Sentiment Analysis/05. Framing the Problem-IsTOnkAKaJw.mp417.65MB

Part 02-Module 01-Lesson 03_RNN's/06. 06 FeedForward A V7 Final-4rCfnWbx8-0.mp417.74MB

Part 02-Module 01-Lesson 03_RNN's/18. 20 RNN BPTT B V5 Final-bUU9BEQw0IA.mp418.1MB

Part 02-Module 01-Lesson 03_RNN's/05. 05 RNN FFNN Reminder B V6 Final-FfPjaGcZODc.mp419.68MB

Part 01-Module 01-Lesson 06_CNN Layers and Feature Visualization/05. Convolutional Layers (Part 2)-LX-yVob3c28.mp419.85MB

Part 07-Module 01-Lesson 01_Sentiment Analysis/16. Understanding Inefficiencies in our Network-4MuS-6ATxCU.mp420.67MB

Part 02-Module 01-Lesson 03_RNN's/02. 01 RNN Intro V6 Final-AIQEqg6F38A.mp420.89MB

Part 02-Module 01-Lesson 03_RNN's/13. 16 RNN B V4 Final-wsif3p5t7CI.mp421.12MB

Part 01-Module 01-Lesson 02_Image Representation & Classification/26. Nd113 C7 32 L Average Brightness V2-oUlOS670uQg.mp421.19MB

Part 02-Module 01-Lesson 03_RNN's/17. 19 RNN BPTT A V6 Final-eE2L3-2wKac.mp421.57MB

Part 02-Module 01-Lesson 03_RNN's/16. 18 RNN Example V5 Final-MDLk3fhpTx0.mp422.11MB

Part 07-Module 01-Lesson 01_Sentiment Analysis/19. Further Noise Reduction-Kl3hWxizKVg.mp422.33MB

Part 01-Module 01-Lesson 02_Image Representation & Classification/08. Images as Grids of Pixels-RVNiaZuv6Ss.mp422.58MB

Part 01-Module 01-Lesson 02_Image Representation & Classification/30. Nd113 C7 46 L Evaluation Metrics-fDN4D1QV674.mp423.75MB

Part 07-Module 01-Lesson 01_Sentiment Analysis/02. Andrew Trask - Intro-da1I0mea1jQ.mp423.76MB

Part 01-Module 01-Lesson 01_Welcome to Computer Vision/05. Meet Danny Shapiro At Nvidia-wm1aZZvF6Is.mp424.21MB

Part 02-Module 01-Lesson 03_RNN's/03. 02 RNN History V4 Final-HbxAnYUfRnc.mp424.26MB

Part 07-Module 01-Lesson 01_Sentiment Analysis/07. Mini Project 1 Solution-l4r5l0HvHRI.mp424.79MB

Part 05-Module 01-Lesson 03_Deep Learning with PyTorch/10. Py Part 8 V1-3eqn5sgCOsY.mp424.88MB

Part 02-Module 01-Lesson 03_RNN's/05. 04 RNN FFNN Reminder A V7 Final-_vrp2lZjXf0.mp425.79MB

Part 09-Module 02-Lesson 01_C++ Intro to Optimization/04. Nd113 Embedded Terminal V1-Bhl5JQ_N9V8.mp426.5MB

Part 02-Module 01-Lesson 03_RNN's/06. 07 FeedForward B V3-kTYbTVh1d0k.mp426.65MB

Part 05-Module 01-Lesson 03_Deep Learning with PyTorch/07. Py Part 5 V2-coBbbrGZXI0.mp427.08MB

Part 05-Module 01-Lesson 03_Deep Learning with PyTorch/05. Py Part 3 V2-u8hDj5aJK6I.mp428.37MB

Part 07-Module 01-Lesson 01_Sentiment Analysis/18. Mini Project 5 Solution-Hv86B_jjWTI.mp428.86MB

Part 07-Module 01-Lesson 01_Sentiment Analysis/22. Analysis What's Going on in the Weights-UHsT35pbpcE.mp433.67MB

Part 03-Module 01-Lesson 04_Introduction to Kalman Filters/25. Kalman Filter Code Solution - Artificial Intelligence for Robotics-X7cixvcogl8.mp433.73MB

Part 05-Module 01-Lesson 03_Deep Learning with PyTorch/04. Py Part 2 V1-u50_ZyKqt8g.mp434.58MB

Part 02-Module 01-Lesson 03_RNN's/08. 08 Backpropagation Theory V6 Final-Xlgd8I3TWUg.mp434.84MB

Part 02-Module 01-Lesson 03_RNN's/25. 23 From RNNs To LSTMs V4 Final-MsqybcWmzGY.mp436.16MB

Part 02-Module 01-Lesson 03_RNN's/10. 12 Backpropagation Example B V6 Final-yiSwuMP2UIA.mp437.06MB

Part 04-Module 01-Lesson 01_Applying Deep Learning Models/02. Navegação de tráfico 3-az5ElmV4DhY.mp438.12MB

Part 07-Module 01-Lesson 01_Sentiment Analysis/21. Mini Project 6 Solution-ji0famK7gOQ.mp439.15MB

Part 07-Module 01-Lesson 01_Sentiment Analysis/14. Understanding Neural Noise-ubqhh4Iv7O4.mp450.21MB

Part 07-Module 01-Lesson 01_Sentiment Analysis/13. Mini Project 3 Solution-imnxzCev4SI.mp454.58MB

Part 09-Module 02-Lesson 03_Project Optimize Histogram Filter/02. Nd113 Running The Project V1--X1pB-HTdnQ.mp480.41MB