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种子名称： Udacity - AI Programming with Python Nanodegree nd089 v1.0.0
文件类型： 视频
文件数目： 326个文件
文件大小： 1.89 GB
收录时间： 2023-3-15 12:35
已经下载： 3次
资源热度： 215
最近下载： 2024-11-13 18:03

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Udacity - AI Programming with Python Nanodegree nd089 v1.0.0.torrent

Part 03-Module 01-Lesson 01_Anaconda/media/conda_enter.mp497.26KB

Part 03-Module 01-Lesson 02_Jupyter Notebooks/media/command+palette.mp4169.16KB

Part 03-Module 01-Lesson 01_Anaconda/media/conda_install.mp4201.72KB

Part 03-Module 01-Lesson 02_Jupyter Notebooks/media/notebook+interface.mp4215.47KB

Part 05-Module 01-Lesson 01_Introduction to Neural Networks/10. DL 10 S Perceptron Algorithm-fATmrG2hQzI.mp4260.01KB

Part 03-Module 01-Lesson 02_Jupyter Notebooks/media/Markdown+cells.mp4330.36KB

Part 05-Module 01-Lesson 03_Training Neural Networks/10. Random Restart-idyBBCzXiqg.mp4394.99KB

Part 08-Module 01-Lesson 05_Tagging, Branching, and Merging/04. Nd016 WebND Ud123 Gitcourse BETAMOJITO L5 54 Content On Different Branches-Px6EUylw8Uw.mp4499.47KB

Part 03-Module 01-Lesson 01_Anaconda/media/conda_default_install.mp4595.3KB

Part 08-Module 02-Lesson 01_Working With Remotes/04. L1 - Git Push In Theory-21TvMEtMRys.mp4656.11KB

Part 08-Module 02-Lesson 01_Working With Remotes/06. Pull Vs Fetch-kxXdk2HcOBo.mp4787.86KB

Part 09-Module 01-Lesson 01_Shell Workshop/09. Ud206 011 Shell P7.1 - Downloading Solution-1oEJUA-b0kE.mp4806.43KB

Part 05-Module 01-Lesson 03_Training Neural Networks/09. Local Minima-gF_sW_nY-xw.mp4819.86KB

Part 08-Module 02-Lesson 01_Working With Remotes/02. L1 - Sending Branches To Remote-414f0ukhOTY.mp4826.62KB

Part 08-Module 02-Lesson 01_Working With Remotes/05. L1 - Git Pull In Theory-MjNU2LTDVAA.mp4898.5KB

Part 08-Module 01-Lesson 01_What is Version Control/03. Nd016 WebND Ud123 Gitcourse BETAMOJITO L1 17 Git The Big Picture 2-rFtUkk-sCqw.mp4908.99KB

Part 05-Module 01-Lesson 03_Training Neural Networks/14. Learning Rate-TwJ8aSZoh2U.mp4927.05KB

Part 05-Module 01-Lesson 01_Introduction to Neural Networks/09. XOR Perceptron-TF83GfjYLdw.mp4947KB

Part 05-Module 01-Lesson 01_Introduction to Neural Networks/08. Why Neural Networks-zAkzOZntK6Y.mp4982.27KB

Part 10-Module 01-Lesson 02_Linear Regression/02. Solution Housing Prices-uhdTulw9-Nc.mp41001.4KB

Part 05-Module 01-Lesson 03_Training Neural Networks/06. DL 53 Q Regularization-KxROxcRsHL8.mp41.01MB

Part 08-Module 01-Lesson 05_Tagging, Branching, and Merging/02. Nd016 WebND Ud123 Gitcourse BETAMOJITO L5 03 Tagging Overview-D4VdXT72ASE.mp41.06MB

Part 10-Module 01-Lesson 02_Linear Regression/03. Fitting A Line-gkdoknEEcaI.mp41.12MB

Part 05-Module 01-Lesson 01_Introduction to Neural Networks/31. Non-Linear Models-HWuBKCZsCo8.mp41.13MB

Part 05-Module 01-Lesson 01_Introduction to Neural Networks/29. Continuous Perceptrons-07-JJ-aGEfM.mp41.13MB

Part 08-Module 02-Lesson 01_Working With Remotes/06. L1 - Fetch Merge And Push-jwyQUfE1Eqw.mp41.29MB

Part 09-Module 01-Lesson 01_Shell Workshop/10. Ud206 013 Shell P8 - Viewing Files-hPPVMKqbQV0.mp41.31MB

Part 05-Module 01-Lesson 03_Training Neural Networks/11. Vanishing Gradient-W_JJm_5syFw.mp41.32MB

Part 03-Module 01-Lesson 05_Matplotlib and Seaborn Part 1/13. DataVis L3 11 V1-C8DGwJa_adA.mp41.32MB

Part 05-Module 01-Lesson 01_Introduction to Neural Networks/12. Non-Linear Regions-B8UrWnHh1Wc.mp41.33MB

Part 08-Module 01-Lesson 05_Tagging, Branching, and Merging/05. Nd016 WebND Ud123 Gitcourse BETAMOJITO L5 71 Merging-gQiWicrreJg.mp41.43MB

Part 05-Module 01-Lesson 01_Introduction to Neural Networks/34. Chain Rule-YAhIBOnbt54.mp41.46MB

Part 10-Module 01-Lesson 02_Linear Regression/01. DLND REG 01 Quiz Housing Prices V2-8CSBiVKu35Q.mp41.48MB

Part 05-Module 01-Lesson 01_Introduction to Neural Networks/23. DL 29 Logistic Regression-Minimizing The Error Function-KayqiYijlzc.mp41.49MB

Part 10-Module 01-Lesson 06_Support Vector Machines/01. SVM 01 Which Line Is Better V1-NCml_NCvd1I.mp41.55MB

Part 02-Module 02-Lesson 01_Lab Classifying Images/02. AIPND Python Lab - Introduction Video-T_cjVqDULQI.mp41.55MB

Part 08-Module 01-Lesson 03_Review a Repo's History/04. Nd016 WebND Ud123 Gitcourse BETAMOJITO L3 33 Git Log Vs Git Log --Stat Walkthru-aOICKP_9xiY.mp41.61MB

Part 10-Module 01-Lesson 03_Logistic Regression/02. Classification Example-46PywnGa_cQ.mp41.62MB

Part 05-Module 01-Lesson 01_Introduction to Neural Networks/04. Classification Example-46PywnGa_cQ.mp41.62MB

Part 05-Module 01-Lesson 01_Introduction to Neural Networks/17. One-Hot Encoding-AePvjhyvsBo.mp41.65MB

Part 08-Module 02-Lesson 03_Staying In Sync With A Remote Repository/02. L3 - Pull Request In Theory-twLr9ndsf90.mp41.65MB

Part 05-Module 01-Lesson 01_Introduction to Neural Networks/33. DL 42 Neural Network Error Function (1)-SC1wEW7TtKs.mp41.72MB

Part 05-Module 01-Lesson 01_Introduction to Neural Networks/16. Quiz - Softmax-NNoezNnAMTY.mp41.73MB

Part 05-Module 01-Lesson 03_Training Neural Networks/16. Error Functions Around the World-34AAcTECu2A.mp41.73MB

Part 09-Module 01-Lesson 01_Shell Workshop/11. Ud206 014 Shell P9 - Removing Things-it19PvJarbk.mp41.74MB

Part 10-Module 01-Lesson 05_Naive Bayes/04. SL NB 08 S Bayesian Learning 2 V1 V6-3rIYZgCXVXY.mp41.8MB

Part 09-Module 01-Lesson 01_Shell Workshop/05. Ud206 006 Shell P3 - Navigating Directories-i9Xp94DmdB8.mp41.82MB

Part 03-Module 01-Lesson 06_Matplotlib and Seaborn Part 2/07. Data Vis L4 C07 V1-f6v3L3IDo24.mp41.83MB

Part 08-Module 01-Lesson 03_Review a Repo's History/03. Nd016 WebND Ud123 Gitcourse BETAMOJITO L3 25 Git Log Vs Git Log --Oneline Walkthru-rn6v_QgYFnU.mp41.85MB

Part 05-Module 01-Lesson 01_Introduction to Neural Networks/19. Quiz Cross Entropy-njq6bYrPqSU.mp41.86MB

Part 05-Module 01-Lesson 01_Introduction to Neural Networks/32. Multiclass Classification-uNTtvxwfox0.mp41.88MB

Part 02-Module 01-Lesson 05_Scripting/17. Reading And Writing Files Using With-OQ-Y0mMjm00.mp41.91MB

Part 05-Module 01-Lesson 01_Introduction to Neural Networks/10. Perceptron Algorithm--zhTROHtscQ.mp41.92MB

Part 05-Module 01-Lesson 01_Introduction to Neural Networks/16. DL 18 S Softmax-n8S-v_LCTms.mp41.95MB

Part 05-Module 01-Lesson 01_Introduction to Neural Networks/25. Gradient Descent Algorithm-snxmBgi_GeU.mp41.98MB

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

Part 09-Module 01-Lesson 01_Shell Workshop/13. Ud206 017 Shell P11 - Variables-Dx3WlMZk8iA.mp42.01MB

Part 09-Module 01-Lesson 01_Shell Workshop/07. Ud206 008 Shell P5 - Parameters-UX9mzq11Mmg.mp42.06MB

Part 05-Module 01-Lesson 01_Introduction to Neural Networks/03. Classsification Example-Dh625piH7Z0.mp42.07MB

Part 10-Module 01-Lesson 03_Logistic Regression/01. Classsification Example-Dh625piH7Z0.mp42.07MB

Part 05-Module 01-Lesson 01_Introduction to Neural Networks/21. Formula For Cross 1-qvr_ego_d6w.mp42.08MB

Part 09-Module 01-Lesson 01_Shell Workshop/04. Ud206 004 Shell P2 - Your First Command-ggf5WhOYy1U.mp42.09MB

Part 08-Module 01-Lesson 06_Undoing Changes/04. Nd016 WebND Ud123 Gitcourse BETAMOJITO L6 17 Soft Vs Medium Vs Hard Walkthrough-UN7ki2G2yKc.mp42.1MB

Part 03-Module 01-Lesson 06_Matplotlib and Seaborn Part 2/12. Data Vis L4 C12 V2-aJncRqqJUYI.mp42.13MB

Part 05-Module 01-Lesson 01_Introduction to Neural Networks/30. Non-Linear Data-F7ZiE8PQiSc.mp42.14MB

Part 05-Module 01-Lesson 03_Training Neural Networks/15. Momentum-r-rYz_PEWC8.mp42.14MB

Part 10-Module 01-Lesson 07_Ensemble Methods/03. MLND SL EM 03 AdaBoost V1 MAIN V1-HD6SRBWKGUE.mp42.17MB

Part 09-Module 01-Lesson 01_Shell Workshop/06. Ud206 007 Shell P4 - Current Working Directory-X7dsy3oMHp0.mp42.18MB

Part 08-Module 01-Lesson 03_Review a Repo's History/02. Nd016 WebND Ud123 Gitcourse BETAMOJITO L3 11 Git Log Output Explained-xJfurQcVYfo.mp42.22MB

Part 05-Module 01-Lesson 01_Introduction to Neural Networks/15. Discrete vs Continuous-rdP-RPDFkl0.mp42.26MB

Part 04-Module 02-Lesson 03_Linear Mapping Lab/04. AIPND Linear Algebra Currency Conversion Problem v2-wmHk5cL5NJA.mp42.29MB

Part 05-Module 01-Lesson 03_Training Neural Networks/12. Other Activation Functions-kA-1vUt6cvQ.mp42.3MB

Part 10-Module 01-Lesson 07_Ensemble Methods/02. MLND SL EM 02 Bagging V1 MAIN V1-9L_B0Jcio3c.mp42.34MB

Part 03-Module 01-Lesson 05_Matplotlib and Seaborn Part 1/05. L3 041 Absolute V Relative Frequency V5-FpnZ7dH4FqU.mp42.41MB

Part 08-Module 02-Lesson 03_Staying In Sync With A Remote Repository/05. L3 - Squashing In Theory-H5JqcdIB5y0.mp42.44MB

Part 04-Module 02-Lesson 03_Linear Mapping Lab/04. AIPND Linear Algebra Matrix Multiplication v2-TavNlmrIuwI.mp42.45MB

Part 05-Module 01-Lesson 02_Implementing Gradient Descent/02. Gradient Descent-29PmNG7fuuM.mp42.46MB

Part 09-Module 01-Lesson 01_Shell Workshop/16. Ud206 021 Shell P14 Aliases-kINmpgXxayM.mp42.46MB

Part 04-Module 01-Lesson 02_Vectors/02. Vectors 2-R7WiQYixvRQ.mp42.52MB

Part 02-Module 02-Lesson 01_Lab Classifying Images/03. AIPND Python Lab - Lab Instructions Video-Pv4yi_OJtuU.mp42.54MB

Part 02-Module 01-Lesson 02_Data Types and Operators/38. Conclusion-LLEZadlXM8A.mp42.54MB

Part 09-Module 01-Lesson 01_Shell Workshop/08. Ud206 009 Shell P6 - Organizing Your Files-NZsYyzzpJXA.mp42.55MB

Part 02-Module 01-Lesson 05_Scripting/05. Running A Python Script-vMKemwCderg.mp42.55MB

Part 05-Module 01-Lesson 01_Introduction to Neural Networks/06. 09 Higher Dimensions-eBHunImDmWw.mp42.59MB

Part 08-Module 01-Lesson 06_Undoing Changes/05. Undoing Changes--_PPVk2UZMU.mp42.59MB

Part 08-Module 02-Lesson 01_Working With Remotes/03. L1 - New Repo Git Commands On GitHub-myuGLZLYpYY.mp42.6MB

Part 08-Module 01-Lesson 01_What is Version Control/03. Nd016 WebND Ud123 Gitcourse BETAMOJITO L1 15 Git The Big Picture-dVil8e0yptQ.mp42.6MB

Part 08-Module 01-Lesson 06_Undoing Changes/06. Course Outro-twn_cheqoK8.mp42.67MB

Part 05-Module 01-Lesson 01_Introduction to Neural Networks/09. AND And OR Perceptrons-45K5N0P9wJk.mp42.68MB

Part 04-Module 02-Lesson 01_Vectors Lab/02. AIPND Linear Algebra Vectors Lab Solution2 v1-UJGRYNl2ZFo.mp42.69MB

Part 08-Module 01-Lesson 01_What is Version Control/02. Nd016 WebND Ud123 Gitcourse BETAMOJITO L1 11 Google Docs Revision History Walkthrough-GcvvbdKEchk.mp42.76MB

Part 08-Module 02-Lesson 01_Working With Remotes/07. Lesson Wrap Up-6Koa4nAu-04.mp42.82MB

Part 05-Module 01-Lesson 01_Introduction to Neural Networks/32. 29 Neural Network Architecture 2-FWN3Sw5fFoM.mp42.83MB

Part 02-Module 01-Lesson 05_Scripting/29. Conclusion-rEMrswkLvh8.mp42.84MB

Part 05-Module 01-Lesson 02_Implementing Gradient Descent/06. Multilayer perceptrons-Rs9petvTBLk.mp42.85MB

Part 06-Module 01-Lesson 01_ Create Your Own Image Classifier/02. PROJECT INTRO MAIN V2---9IFCNBM6Y.mp42.85MB

Part 05-Module 01-Lesson 01_Introduction to Neural Networks/11. Perceptron Agorithm Pseudocode-p8Q3yu9YqYk.mp42.87MB

Part 03-Module 01-Lesson 05_Matplotlib and Seaborn Part 1/09. L3 081 Histograms V2-RLez9L0htGQ.mp42.88MB

Part 04-Module 02-Lesson 03_Linear Mapping Lab/04. AIPND Linear Algebra Plotting a Transformed Vector v3-lmF-V8emukA.mp42.88MB

Part 10-Module 01-Lesson 06_Support Vector Machines/02. SVM 02 Minimizing Distances V1-mNKk2dBsNGA.mp42.91MB

Part 08-Module 01-Lesson 02_Create A Git Repo/05. Create A Repo - Outro-h7j4STDFCjs.mp42.96MB

Part 05-Module 01-Lesson 03_Training Neural Networks/02. Training Optimization-UiGKhx9pUYc.mp42.96MB

Part 08-Module 02-Lesson 03_Staying In Sync With A Remote Repository/03. L3 - Include Upstream Changes-VvoC6hN6FjU.mp43.01MB

Part 05-Module 01-Lesson 01_Introduction to Neural Networks/19. Quiz - Cross 1--xxrisIvD0E.mp43.02MB

Part 03-Module 01-Lesson 06_Matplotlib and Seaborn Part 2/06. Data Vis L4 C06 V2-f8Kh4PByiEA.mp43.02MB

Part 09-Module 01-Lesson 01_Shell Workshop/03. Ud206 003 Shell P1 - Opening A Terminal-4q6Vtym-nno.mp43.02MB

Part 03-Module 01-Lesson 05_Matplotlib and Seaborn Part 1/14. DataVis L3 12 V2-fo0VIbQRBJk.mp43.05MB

Part 09-Module 01-Lesson 01_Shell Workshop/12. Ud206 016 Shell P10 - Searching And Pipes-AWpVScp9z4s.mp43.1MB

Part 02-Module 01-Lesson 03_Control Flow/34. Congrats!-vDoqpwCHxs4.mp43.11MB

Part 05-Module 01-Lesson 01_Introduction to Neural Networks/32. Layers-pg99FkXYK0M.mp43.11MB

Part 09-Module 01-Lesson 01_Shell Workshop/14. Ud206 018 P12 Startup Files (.bash_profile)--zF-XebfzBE.mp43.12MB

Part 03-Module 01-Lesson 06_Matplotlib and Seaborn Part 2/11. Data Vis L4 C11 V1-3Ls6w8Cd8n4.mp43.15MB

Part 02-Module 01-Lesson 05_Scripting/13. Handling Error Specifying Exceptions-EHW5I7shdJg.mp43.15MB

Part 09-Module 01-Lesson 01_Shell Workshop/09. Ud206 011 Shell P7 - Downloading-h7FhU1f4TgE.mp43.16MB

Part 05-Module 01-Lesson 01_Introduction to Neural Networks/28. Gradient Descent Vs Perceptron Algorithm-uL5LuRPivTA.mp43.2MB

Part 08-Module 02-Lesson 03_Staying In Sync With A Remote Repository/01. Intro-j5RmK0UHOTY.mp43.22MB

Part 03-Module 01-Lesson 06_Matplotlib and Seaborn Part 2/04. Data Vis L4 C04 V1-O6ElT4IFXc0.mp43.24MB

Part 08-Module 02-Lesson 01_Working With Remotes/05. L1 - Adding A Commit On GitHub-UBYxcTg6VLU.mp43.29MB

Part 04-Module 02-Lesson 01_Vectors Lab/02. AIPND Linear Algebra Vectors Lab Solution1 v1-xk-JNxMzlsQ.mp43.29MB

Part 05-Module 01-Lesson 01_Introduction to Neural Networks/34. Calculating The Gradient 1 -tVuZDbUrzzI.mp43.31MB

Part 05-Module 01-Lesson 04_Deep Learning with PyTorch/06. PyTorch - Part 4-AEJV_RKZ7VU.mp43.32MB

Part 03-Module 01-Lesson 06_Matplotlib and Seaborn Part 2/06. L4 061 Violin Plots 2 V3-0hr61L-LZyM.mp43.32MB

Part 03-Module 01-Lesson 06_Matplotlib and Seaborn Part 2/01. L4 011 Intro V2-JzvJIWG8Rk4.mp43.36MB

Part 10-Module 01-Lesson 07_Ensemble Methods/01. MLND SL EM 01 Intro V1 MAIN V2-5v9KqIo6CFE.mp43.38MB

Part 02-Module 01-Lesson 05_Scripting/11. Errors And Exceptions-DmthSiy2d0U.mp43.39MB

Part 09-Module 01-Lesson 01_Shell Workshop/17. Ud206 022 Shell Workshop Outro-68twTPXPrx0.mp43.4MB

Part 08-Module 02-Lesson 02_Working On Another Developer's Repository/01. Intro-VkqtlJuZ9rs.mp43.4MB

Part 02-Module 02-Lesson 01_Lab Classifying Images/07. AIPND Python Lab - Timing Code Solution Video-ic7gqM4cnl4.mp43.41MB

Part 05-Module 01-Lesson 02_Implementing Gradient Descent/07. Backpropagation-MZL97-2joxQ.mp43.44MB

Part 08-Module 01-Lesson 01_What is Version Control/06. Onward-iXbMaTwfIJI.mp43.51MB

Part 03-Module 01-Lesson 04_Pandas/06. Pandas 3 V1-yhMT0X6YPFA.mp43.51MB

Part 05-Module 01-Lesson 01_Introduction to Neural Networks/13. Error Functions-YfUUunxWIJw.mp43.54MB

Part 08-Module 01-Lesson 05_Tagging, Branching, and Merging/03. Nd016 WebND Ud123 Gitcourse BETAMOJITO L5 26 Branching Overview-ywcOC6CLG4s.mp43.55MB

Part 03-Module 01-Lesson 06_Matplotlib and Seaborn Part 2/02. Data Vis L4 C02 V1-wBDC5AmYgyg.mp43.58MB

Part 08-Module 01-Lesson 01_What is Version Control/04. Nd016 WebND Ud123 Gitcourse BETAMOJITO L1 23 Configure Terminal-h00n9QLfbqU.mp43.63MB

Part 03-Module 01-Lesson 05_Matplotlib and Seaborn Part 1/16. L3 141 Lesson Summary V1-7ZaSMbsJUWU.mp43.63MB

Part 05-Module 01-Lesson 01_Introduction to Neural Networks/10. 07 Perceptron Algorithm Trick-lif_qPmXvWA.mp43.66MB

Part 09-Module 01-Lesson 01_Shell Workshop/15. Ud206 020 Shell P13 Controlling The Shell Prompt ($PS1)-nnqvRZ-Fx3k.mp43.73MB

Part 04-Module 02-Lesson 04_Linear Algebra in Neural Networks/05. LinearAlgebra 05 RNN FFNN Reminder PAIND 82mp4 V1-SSgQRH-V-1k.mp43.73MB

Part 03-Module 01-Lesson 06_Matplotlib and Seaborn Part 2/09. Data Vis L4 C09 V1-OnzWhpgM9Vs.mp43.74MB

Part 03-Module 01-Lesson 06_Matplotlib and Seaborn Part 2/13. Data Vis L4 C13 V1-Z7NjwA6jbjU.mp43.75MB

Part 03-Module 01-Lesson 06_Matplotlib and Seaborn Part 2/03. Data Vis L4 C03 V1-0F6ldBC6Nbs.mp43.75MB

Part 05-Module 01-Lesson 01_Introduction to Neural Networks/24. Gradient Descent-rhVIF-nigrY.mp43.76MB

Part 03-Module 01-Lesson 04_Pandas/05. Pandas 2 V1-B7MuFIwboKU.mp43.77MB

Part 08-Module 01-Lesson 01_What is Version Control/05. Nd016 WebND Ud123 Gitcourse BETAMOJITO L1 30 Configure Terminal-CCYjHfBk9hw.mp43.77MB

Part 08-Module 01-Lesson 05_Tagging, Branching, and Merging/07. Outro-ot4fPX1jzOI.mp43.8MB

Part 03-Module 01-Lesson 04_Pandas/04. Pandas 1 V1-iXnYN8cnhzs.mp43.8MB

Part 03-Module 01-Lesson 06_Matplotlib and Seaborn Part 2/13. L4 131 Line Plots V1-kSntEWPuOa0.mp43.82MB

Part 05-Module 01-Lesson 01_Introduction to Neural Networks/18. Maximum Likelihood 2-6nUUeQ9AeUA.mp43.85MB

Part 05-Module 01-Lesson 01_Introduction to Neural Networks/05. Linear Boundaries-X-uMlsBi07k.mp43.85MB

Part 03-Module 01-Lesson 05_Matplotlib and Seaborn Part 1/02. L3 011 Intro V3-4BpAF4MYKm8.mp43.85MB

Part 05-Module 01-Lesson 03_Training Neural Networks/13. Batch vs Stochastic Gradient Descent-2p58rVgqsgo.mp43.95MB

Part 02-Module 01-Lesson 02_Data Types and Operators/27. L2 04 Tuples V3-33xN-AbTMoc.mp43.96MB

Part 08-Module 02-Lesson 03_Staying In Sync With A Remote Repository/06. Course Wrap Up-66Ut8Bv6kgc.mp44MB

Part 05-Module 01-Lesson 01_Introduction to Neural Networks/16. DL 18 Q Softmax V2-RC_A9Tu99y4.mp44.01MB

Part 03-Module 01-Lesson 06_Matplotlib and Seaborn Part 2/07. L4 071 Box Plots V4-3gxJag12T0g.mp44.02MB

Part 02-Module 01-Lesson 01_Why Python Programming/03. L1 03 Programming In Python V4-O1cTNYAjeeg.mp44.03MB

Part 08-Module 02-Lesson 01_Working With Remotes/02. L1 - Remote Repos Intro-AnSlYftJnwA.mp44.11MB

Part 05-Module 01-Lesson 01_Introduction to Neural Networks/22. DL 27 Multi-Class Cross Entropy 2 Fix-keDswcqkees.mp44.14MB

Part 10-Module 01-Lesson 04_Decision Trees/04. MLND SL DT 04 Q Student Admissions V3 MAIN V1-MOa335cQGI4.mp44.16MB

Part 03-Module 01-Lesson 06_Matplotlib and Seaborn Part 2/12. L4 121 Adaptations Of Univariate Plots V3-MXcqplnUB0o.mp44.18MB

Part 10-Module 01-Lesson 04_Decision Trees/02. MLND SL DT 02 Recommending Apps 2 MAIN V3-KSrIYqKZwCA.mp44.19MB

Part 02-Module 01-Lesson 02_Data Types and Operators/35. L2 01 Compound Data Structures V1-jmQ8IKvQgBU.mp44.21MB

Part 05-Module 01-Lesson 03_Training Neural Networks/08. Dropout-Ty6K6YiGdBs.mp44.22MB

Part 03-Module 01-Lesson 06_Matplotlib and Seaborn Part 2/09. L4 091 Clustered Bar Charts V4-0rFp55TtEJM.mp44.22MB

Part 05-Module 01-Lesson 01_Introduction to Neural Networks/20. Cross Entropy 1-iREoPUrpXvE.mp44.22MB

Part 08-Module 01-Lesson 03_Review a Repo's History/03. Nd016 WebND Ud123 Gitcourse BETAMOJITO L3 27 Confession Corner-xtsugblSwrU.mp44.23MB

Part 02-Module 01-Lesson 05_Scripting/01. Scripting-Qxe_gCiXUDg.mp44.24MB

Part 02-Module 01-Lesson 05_Scripting/13. Handling Errors Try Except Finally-S6hwBZG0KwM.mp44.24MB

Part 03-Module 01-Lesson 06_Matplotlib and Seaborn Part 2/04. L4 041 Heat Maps V4-RyCdvsmBjtE.mp44.3MB

Part 03-Module 01-Lesson 05_Matplotlib and Seaborn Part 1/05. DataVis L3 04 V2-HLum_ys7RJ0.mp44.32MB

Part 03-Module 01-Lesson 03_NumPy/03. NumPy 0 V1-vyjMs8KFHlE.mp44.35MB

Part 08-Module 01-Lesson 03_Review a Repo's History/07. A Repository's History - Outro-9rUf2HbdAd8.mp44.39MB

Part 08-Module 01-Lesson 01_What is Version Control/01. Gitfinal L1 03 Version Control Systems-b7TjsVoTo3Q.mp44.39MB

Part 08-Module 02-Lesson 03_Staying In Sync With A Remote Repository/05. L3 - Squashing Introduction-mRbeT2XVL9w.mp44.4MB

Part 09-Module 01-Lesson 01_Shell Workshop/02. Ud206 002 P0 Windows Installing Git Bash-UQZvV6VTlGQ.mp44.41MB

Part 02-Module 01-Lesson 04_Functions/18. Conclusion-QRnLr7pwHyk.mp44.48MB

Part 08-Module 02-Lesson 03_Staying In Sync With A Remote Repository/02. L3 - Pull Request In Action-d3AGtKmHxUk.mp44.57MB

Part 04-Module 02-Lesson 04_Linear Algebra in Neural Networks/06. Linear Algebra 06 FeedForward A V7 PAIND83 V1-kQ6rNndcA1I.mp44.58MB

Part 03-Module 01-Lesson 05_Matplotlib and Seaborn Part 1/13. L3 111 Descriptive Stats Outliers And Axis Limits V2-kQoK7UwrGh0.mp44.6MB

Part 03-Module 01-Lesson 06_Matplotlib and Seaborn Part 2/11. L4 111 Faceting V2-oUYRqI6wFGw.mp44.63MB

Part 03-Module 01-Lesson 06_Matplotlib and Seaborn Part 2/03. L4 031 Overplotting Transparency And Jitter 1 V4-BGqR-nxgMtg.mp44.66MB

Part 05-Module 01-Lesson 01_Introduction to Neural Networks/32. Combinando modelos-Boy3zHVrWB4.mp44.73MB

Part 10-Module 01-Lesson 04_Decision Trees/01. MLND SL DT 01 Recommending Apps 1 MAIN V3-uI_yNrqqKVg.mp44.8MB

Part 02-Module 01-Lesson 02_Data Types and Operators/22. L2 07 Lists And Membership Operators II V3-3Nj-b-ZzqH8.mp44.83MB

Part 05-Module 01-Lesson 01_Introduction to Neural Networks/23. Error Function-V5kkHldUlVU.mp44.84MB

Part 03-Module 01-Lesson 05_Matplotlib and Seaborn Part 1/14. L3 121 Scales And Transformations V3-PE53ga2bOME.mp44.85MB

Part 04-Module 01-Lesson 02_Vectors/01. Vectors 1-oPBz-MLVUHk.mp44.88MB

Part 02-Module 02-Lesson 01_Lab Classifying Images/08. AIPND Python Lab - Command Line Arguments Solutions Video-tuBIyuPrXFY.mp44.9MB

Part 05-Module 01-Lesson 03_Training Neural Networks/05. Model Complexity Graph-NnS0FJyVcDQ.mp44.9MB

Part 08-Module 01-Lesson 04_Add Commits To A Repo/07. Outro-5eyvsMvAPYs.mp44.96MB

Part 02-Module 01-Lesson 05_Scripting/24. Techniques For Importing Modules Part II-aASigWQ_XU0.mp45MB

Part 08-Module 01-Lesson 01_What is Version Control/03. Nd016 WebND Ud123 Gitcourse BETAMOJITO L1 18 Recap-xqD9ImXXXHk.mp45.03MB

Part 10-Module 01-Lesson 06_Support Vector Machines/08. SVM 13 RBF Kernel 2 V1-ozl9UWVP0MI.mp45.06MB

Part 03-Module 01-Lesson 03_NumPy/09. NumPy 5 V1-vGjI-WTnEbY.mp45.09MB

Part 05-Module 01-Lesson 01_Introduction to Neural Networks/07. DL 06 Perceptron Definition Fix V2-hImSxZyRiOw.mp45.13MB

Part 03-Module 01-Lesson 05_Matplotlib and Seaborn Part 1/09. DataVis L3 08 V2-f1we_0dUSXg.mp45.17MB

Part 02-Module 01-Lesson 01_Why Python Programming/02. L1 01 Intro V3-yyNtiUyI5Tw.mp45.21MB

Part 02-Module 01-Lesson 05_Scripting/08. Scripting With Raw Input-Fs9uLV2qfgI.mp45.25MB

Part 03-Module 01-Lesson 06_Matplotlib and Seaborn Part 2/02. L4 021 Scatterplots And Correlation V2-wqMwTDVT9_Y.mp45.26MB

Part 02-Module 01-Lesson 02_Data Types and Operators/25. L2 05 Lists Methods V1-WXkPm4rv6ng.mp45.28MB

Part 08-Module 02-Lesson 02_Working On Another Developer's Repository/02. Forking a Repository - What Is Forking-z4mkVwqVztc.mp45.29MB

Part 02-Module 01-Lesson 05_Scripting/24. Techniques For Importing Modules-jPGyFgcIvsM.mp45.33MB

Part 05-Module 01-Lesson 01_Introduction to Neural Networks/33. DL 41 Feedforward FIX V2-hVCuvMGOfyY.mp45.33MB

Part 05-Module 01-Lesson 01_Introduction to Neural Networks/15. Discrete vs. Continuous-Rm2KxFaPiJg.mp45.35MB

Part 02-Module 02-Lesson 01_Lab Classifying Images/11. AIPND Python Lab - Check Images Solutions Video-2jaZfP7otSs.mp45.36MB

Part 03-Module 01-Lesson 06_Matplotlib and Seaborn Part 2/15. L4 151 Lesson Summary V1-5igqM44KEmw.mp45.39MB

Part 10-Module 01-Lesson 04_Decision Trees/05. Student Admissions-TdgBi6LtOB8.mp45.41MB

Part 04-Module 02-Lesson 04_Linear Algebra in Neural Networks/07. LinearAlgebra 07 FeedForward PAIND85 V3-pvF6jpS_-cU.mp45.54MB

Part 02-Module 01-Lesson 05_Scripting/27. Experimenting With An Interpreter-hspPtnQwMPg.mp45.58MB

Part 02-Module 01-Lesson 04_Functions/02. Default Arguments-cG6UfBZX2KI.mp45.64MB

Part 02-Module 01-Lesson 02_Data Types and Operators/22. L2 09 Lists And Membership Operators V2-rNV_E50wcWM.mp45.67MB

Part 05-Module 01-Lesson 01_Introduction to Neural Networks/34. DL 46 Calculating The Gradient 2 V2 (2)-7lidiTGIlN4.mp45.69MB

Part 05-Module 01-Lesson 01_Introduction to Neural Networks/18. Maximum Likelihood 1-1yJx-QtlvNI.mp45.75MB

Part 10-Module 01-Lesson 06_Support Vector Machines/03. SVM 03 Error Function V1-l-ahImxoi-U.mp45.88MB

Part 02-Module 01-Lesson 03_Control Flow/01. Introduction-eUrvACMMJ5w.mp45.9MB

Part 02-Module 01-Lesson 05_Scripting/17. Reading And Writing Files Part II-1GRv1S6K8gQ.mp45.92MB

Part 02-Module 01-Lesson 02_Data Types and Operators/29. L2 03 Sets V2-eIHNFgTFfnA.mp45.92MB

Part 03-Module 01-Lesson 05_Matplotlib and Seaborn Part 1/08. L3 071 Pie Charts V3-kSrJGJHTKV8.mp46.05MB

Part 02-Module 01-Lesson 02_Data Types and Operators/22. L2 08 Lists And Membership Operators V2-JAbZdZg5_x8.mp46.06MB

Part 10-Module 01-Lesson 05_Naive Bayes/03. SL NB 07 Q Bayesian Learning 1 V1 V4-J4BmsKXPnkA.mp46.09MB

Part 08-Module 01-Lesson 03_Review a Repo's History/05. Nd016 WebND Ud123 Gitcourse BETAMOJITO L3 42 Git Log -P Output Walkthru-A8Kwocr-K8c.mp46.19MB

Part 04-Module 01-Lesson 02_Vectors/03. Vectors 3-mWV_MpEjz9c.mp46.29MB

Part 08-Module 01-Lesson 06_Undoing Changes/01. Undoing Changes - Intro-Kfi7l41wUVc.mp46.31MB

Part 10-Module 01-Lesson 04_Decision Trees/03. Recommending Apps-nEvW8B1HNq4.mp46.32MB

Part 03-Module 01-Lesson 05_Matplotlib and Seaborn Part 1/04. L3 031 Bar Charts V3-ybXcduB6cXA.mp46.41MB

Part 05-Module 01-Lesson 03_Training Neural Networks/04. Underfitting And Overfitting-xj4PlXMsN-Y.mp46.42MB

Part 05-Module 01-Lesson 01_Introduction to Neural Networks/34. Backpropagation V2-1SmY3TZTyUk.mp46.52MB

Part 04-Module 02-Lesson 02_Linear Combination Lab/02. AIPND Linear Algebra Linear Combination Solution v2-eMYcAqnR8N4.mp46.55MB

Part 08-Module 01-Lesson 05_Tagging, Branching, and Merging/01. Tagging, Branching, And Merging - Intro-sMf_r4_z-Ls.mp46.59MB

Part 05-Module 01-Lesson 01_Introduction to Neural Networks/21. CrossEntropy V1-1BnhC6e0TFw.mp46.61MB

Part 03-Module 01-Lesson 03_NumPy/11. NumPy 6 V1-wtLRuGK0kW4.mp46.61MB

Part 02-Module 01-Lesson 05_Scripting/02. Python Installation-2_P05aYChqQ.mp46.71MB

Part 10-Module 01-Lesson 01_Intro/01. Introduction-bYeteZQrUcE.mp46.79MB

Part 08-Module 01-Lesson 02_Create A Git Repo/01. Creating New Repositories - Intro-KT163BkqIeg.mp46.8MB

Part 03-Module 01-Lesson 04_Pandas/08. Pandas 4 V1-eMHUn9v9dds.mp46.93MB

Part 03-Module 01-Lesson 05_Matplotlib and Seaborn Part 1/04. DataVis L3 03 V2-srRhFrSPdvs.mp46.98MB

Part 10-Module 01-Lesson 06_Support Vector Machines/04. SVM 09 Polynomial Kernel 1 V1-8t2tVDHNBnk.mp47.08MB

Part 03-Module 01-Lesson 02_Jupyter Notebooks/02. Jupyter-qiYDWFLyXvg.mp47.12MB

Part 05-Module 01-Lesson 01_Introduction to Neural Networks/14. Error Functions-jfKShxGAbok.mp47.21MB

Part 02-Module 01-Lesson 05_Scripting/26. Third Party Libraries And Package Managers-epOze9gC6T4.mp47.36MB

Part 02-Module 01-Lesson 05_Scripting/06. Programming Environment Setup-EKxDnCK0NAk.mp47.42MB

Part 02-Module 02-Lesson 01_Lab Classifying Images/15. AIPND Python Lab - Calculate Results Solutions Video-b8dsDty8HDc.mp47.48MB

Part 08-Module 01-Lesson 04_Add Commits To A Repo/01. Adding Commits To A Repo - Intro-sLcOFQ4mGvo.mp47.48MB

Part 03-Module 01-Lesson 03_NumPy/04. NumPy 1 V1-EOHW29kDg7w.mp47.53MB

Part 05-Module 01-Lesson 01_Introduction to Neural Networks/02. Introduction-tn-CrUTkCUc.mp47.54MB

Part 05-Module 01-Lesson 03_Training Neural Networks/07. Regularization-ndYnUrx8xvs.mp47.57MB

Part 08-Module 02-Lesson 02_Working On Another Developer's Repository/02. L2 - Pushing To A Fork-WRgNpr19t48.mp47.65MB

Part 02-Module 01-Lesson 03_Control Flow/02. Indentation-G8qUNOTHtrM.mp47.65MB

Part 03-Module 01-Lesson 04_Pandas/09. Pandas 5 V1-lClsJnZn_7w.mp47.85MB

Part 03-Module 01-Lesson 04_Pandas/10. Pandas 6 V1-GS1kj04XQcM.mp47.87MB

Part 01-Module 01-Lesson 01_Welcome to AI Programming with Python/02. AIPND Instructors FINAL V5-h0_y3eb_3m4.mp47.96MB

Part 02-Module 01-Lesson 04_Functions/11. L4 08 Lambda Expressions V3-wkEmPz1peJM.mp47.99MB

Part 03-Module 01-Lesson 04_Pandas/12. Pandas 7 V1-ruTYp-twXO0.mp48.09MB

Part 08-Module 02-Lesson 03_Staying In Sync With A Remote Repository/05. L3 - Squashing In Action-cL6ehKtJLUM.mp48.16MB

Part 02-Module 02-Lesson 01_Lab Classifying Images/04. AIPND Python Lab - Workspace How-to Video-EQTttywUnXQ.mp48.21MB

Part 02-Module 02-Lesson 01_Lab Classifying Images/14. AIPND Python Lab - Solutions Video-Jfsbtm6yPXY.mp48.24MB

Part 04-Module 01-Lesson 03_Linear Combination/01. Linear Combinations 1-fmal7UE7dEE.mp48.3MB

Part 08-Module 02-Lesson 01_Working With Remotes/01. Intro-SBUOhyXcR1Q.mp48.34MB

Part 02-Module 02-Lesson 01_Lab Classifying Images/09. AIPND Python Lab - Mutable Data Types and Functions Video-LIOmuZdLymw.mp48.35MB

Part 02-Module 01-Lesson 01_Why Python Programming/04. L1 02 Course Overview V4-vFxXSIV5cHM.mp48.37MB

Part 10-Module 01-Lesson 05_Naive Bayes/01. SL NB 01 Guess The Person V1 V1-tAOAjI-7ins.mp48.49MB

Part 03-Module 01-Lesson 03_NumPy/07. NumPy 3 V1-Rt4aydeo9F8.mp48.5MB

Part 04-Module 01-Lesson 01_Introduction/03. Essence Of Linear Algebra Intro -EHcxDZpeGFg.mp48.6MB

Part 04-Module 02-Lesson 04_Linear Algebra in Neural Networks/03. Dolly Inside Head 1 -tyam5ZncjNw.mp48.69MB

Part 02-Module 02-Lesson 01_Lab Classifying Images/13. AIPND Python Lab - Classify Images Solutions Video-sBbY6HmJG9M.mp48.76MB

Part 02-Module 01-Lesson 04_Functions/01. Introduction-p5L4rTV1Pgk.mp48.85MB

Part 08-Module 01-Lesson 01_What is Version Control/01. Gitfinal L1 01 Welcome-lbR82UD5F0c.mp48.89MB

Part 02-Module 01-Lesson 04_Functions/05. Variable Scope-rYubQlAM-gw.mp49.01MB

Part 02-Module 02-Lesson 01_Lab Classifying Images/16. AIPND Python Lab - Printing Results Solutions Video-XRnoQry3ubU.mp49.22MB

Part 10-Module 01-Lesson 06_Support Vector Machines/09. SVM 14 RBF Kernel 3 V1-DctkE8kaWPY.mp49.26MB

Part 02-Module 01-Lesson 02_Data Types and Operators/16. Type Type Conversion-yN6Fam_vZrU.mp49.4MB

Part 01-Module 01-Lesson 01_Welcome to AI Programming with Python/01. AIPND Intro FINAL-CeXA-uzNFp4.mp49.61MB

Part 11-Module 01-Lesson 01_Visualizing The Importance Of The Learning Rate/01. 学习率简介-HLMjeDez7ps.mp49.62MB

Part 10-Module 01-Lesson 06_Support Vector Machines/05. SVM 10 Polynomial Kernel 2 V2-9RfFvZ9DIRg.mp49.69MB

Part 07-Module 01-Lesson 01_How Do I Continue From Here/01. Next Steps Into The AI World Outro-40CCUu30w8c.mp49.71MB

Part 10-Module 01-Lesson 08_Outro/01. Conclusion-hJEuaOUu2yA.mp49.75MB

Part 03-Module 01-Lesson 03_NumPy/08. NumPy 4 V1-jeU7lLgyMms.mp49.8MB

Part 02-Module 01-Lesson 02_Data Types and Operators/05. Assignment Operators-p_qfzL-x3Cs.mp410.15MB

Part 03-Module 01-Lesson 01_Anaconda/02. Why Anaconda-VXukXZv7SCQ.mp410.29MB

Part 08-Module 01-Lesson 01_What is Version Control/03. Gitfinal L1 13 Git'S Terminology-bf26adzeqMM.mp410.33MB

Part 02-Module 01-Lesson 05_Scripting/21. The Standard Library-Fw3vf0tDrJM.mp410.55MB

Part 02-Module 01-Lesson 02_Data Types and Operators/31. L2 02 Dictionaries And Identiy Operators V3-QR8HTxCTWi0.mp410.7MB

Part 09-Module 01-Lesson 01_Shell Workshop/01. Shell Intro--EtN5oD8MM0.mp410.76MB

Part 02-Module 01-Lesson 05_Scripting/17. Reading And Writing Files-w-ZG6DMkVi4.mp410.81MB

Part 02-Module 01-Lesson 03_Control Flow/20. L3 08 While Loops V3-7Sf5tcPlKQw.mp410.89MB

Part 02-Module 01-Lesson 02_Data Types and Operators/02. Arithmetic Operators-M8TIOK2P2yw.mp411.07MB

Part 05-Module 01-Lesson 02_Implementing Gradient Descent/03. Gradient Descent-Math-7sxA5Ap8AWM.mp411.25MB

Part 02-Module 01-Lesson 05_Scripting/20. Importing Files-qjeSn6zZbR0.mp411.41MB

Part 08-Module 01-Lesson 03_Review a Repo's History/01. A Repository's History - Intro-UBmg3syQS0E.mp412.31MB

Part 02-Module 01-Lesson 03_Control Flow/07. Truth Value Testing-e52uw7ejV8k.mp412.78MB

Part 02-Module 01-Lesson 03_Control Flow/25. Break and Continue-F6qJAv9ts9Y.mp413.22MB

Part 02-Module 01-Lesson 02_Data Types and Operators/01. Introduction-4F7SC0C6tfQ.mp413.27MB

Part 02-Module 01-Lesson 02_Data Types and Operators/25. L2 06 Lists Methods V1-tz2Ja1Eaeqo.mp413.33MB

Part 04-Module 01-Lesson 04_Linear Transformation and Matrices/10. Linear Transformations 2-imtEd8M6__s.mp413.49MB

Part 05-Module 01-Lesson 04_Deep Learning with PyTorch/03. Part 1 V2-n4mbZYIfKb4.mp413.81MB

Part 04-Module 01-Lesson 03_Linear Combination/02. Linear Combinations 2-RsKJNDTb8nw.mp414.17MB

Part 03-Module 01-Lesson 03_NumPy/05. NumPy 2 V1-KR3hHf9Zxxg.mp414.18MB

Part 05-Module 01-Lesson 04_Deep Learning with PyTorch/09. PyTorch - Part 7-hFu7GTfRWks.mp414.62MB

Part 02-Module 01-Lesson 03_Control Flow/07. Complex Boolean Expressions-gWmIKWgzFqI.mp415.06MB

Part 02-Module 01-Lesson 02_Data Types and Operators/05. Variables-7pxpUot4x0w.mp415.33MB

Part 02-Module 01-Lesson 02_Data Types and Operators/08. Números inteiros e floats-MiJ1vfWp-Ts.mp415.41MB

Part 02-Module 01-Lesson 04_Functions/02. Defining Functions-IP_tJYhynbc.mp415.48MB

Part 02-Module 01-Lesson 03_Control Flow/28. Zip and Enumerate-bSJPzVArE7M.mp415.71MB

Part 02-Module 01-Lesson 04_Functions/08. Documentation-_Vl9NJkA6JQ.mp415.93MB

Part 05-Module 01-Lesson 04_Deep Learning with PyTorch/08. Py Part 6 V1-HiTih59dCWQ.mp415.94MB

Part 02-Module 01-Lesson 02_Data Types and Operators/05. L2 04b Variables II V3-4IJqbP8vi6A.mp416.81MB

Part 02-Module 01-Lesson 03_Control Flow/02. If Statements-jWiIUMrwPqA.mp416.99MB

Part 02-Module 01-Lesson 02_Data Types and Operators/13. Strings-ySZDrs-nNqg.mp417.26MB

Part 02-Module 01-Lesson 03_Control Flow/31. List Comprehensions-6qxo-NV9v_s.mp417.37MB

Part 02-Module 01-Lesson 03_Control Flow/02. If Elif and Else-KZubH5XT0eU.mp418.28MB

Part 02-Module 01-Lesson 03_Control Flow/10. For Loops-UtX0PXSUCdY.mp418.44MB

Part 10-Module 01-Lesson 06_Support Vector Machines/07. SVM 12 RBF Kernel 1 V3-xdkIulxXWfQ.mp418.6MB

Part 02-Module 01-Lesson 04_Functions/14. Iterators And Generators-tYH8X4Zeh-0.mp418.95MB

Part 02-Module 01-Lesson 03_Control Flow/07. Good And Bad Examples-95oLh3WtdhY.mp419.91MB

Part 04-Module 01-Lesson 04_Linear Transformation and Matrices/11. Linear Transformations 3-g_yTyRwMzXU.mp420.09MB

Part 04-Module 01-Lesson 04_Linear Transformation and Matrices/09. Linear Transformations 1-99jYIxBRDww.mp420.77MB

Part 02-Module 01-Lesson 02_Data Types and Operators/08. Whitespace-UxkIwcOczQQ.mp420.96MB

Part 10-Module 01-Lesson 05_Naive Bayes/02. SL NB 03 Guess The Person Now V1 V2-pQgO1KF90yU.mp421.06MB

Part 02-Module 01-Lesson 02_Data Types and Operators/10. Boolean Comparison and Logical Operators-iNNsUJIDtVU.mp421.62MB

Part 02-Module 01-Lesson 02_Data Types and Operators/19. String Methods-Bv7CAxVOONs.mp423.75MB

Part 05-Module 01-Lesson 04_Deep Learning with PyTorch/10. Py Part 8 V1-3eqn5sgCOsY.mp424.88MB

Part 10-Module 01-Lesson 06_Support Vector Machines/06. SVM 11 Polynomial Kernel 3 V1-XmbK8OjbX5U.mp426.81MB

Part 05-Module 01-Lesson 04_Deep Learning with PyTorch/07. Py Part 5 V2-coBbbrGZXI0.mp427.08MB

Part 05-Module 01-Lesson 04_Deep Learning with PyTorch/05. Py Part 3 V2-u8hDj5aJK6I.mp428.37MB

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