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种子名称： [CourseClub.NET] UDACITY - NLP Foundations Nanodegree
文件类型： 视频
文件数目： 200个文件
文件大小： 1.02 GB
收录时间： 2019-8-5 16:45
已经下载： 3次
资源热度： 140
最近下载： 2024-5-25 07:44

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[CourseClub.NET] UDACITY - NLP Foundations Nanodegree.torrent

Part 01-Module 01-Lesson 01_Intro to Natural Language Processing/01. Welcome to NLP-g-AlFF61p0I.mp44.97MB

Part 01-Module 01-Lesson 01_Intro to Natural Language Processing/02. Structured Languages-NsmqUIHlk6U.mp45.36MB

Part 01-Module 01-Lesson 01_Intro to Natural Language Processing/03. Grammar-Jw3dA7xmoQ4.mp42.14MB

Part 01-Module 01-Lesson 01_Intro to Natural Language Processing/04. Unstructured Text-OmwSdaec5vU.mp44.63MB

Part 01-Module 01-Lesson 01_Intro to Natural Language Processing/06. Context-J-4pfu2w1C0.mp44.62MB

Part 01-Module 01-Lesson 01_Intro to Natural Language Processing/07. Natural Language Processing-sQiURKPFXNM.mp415.48MB

Part 01-Module 01-Lesson 01_Intro to Natural Language Processing/08. Applications of NLP-33dq-H6U4AI.mp427.97MB

Part 01-Module 01-Lesson 01_Intro to Natural Language Processing/09. NLP H 8-LMvKyA3ZBZE.mp430.44MB

Part 01-Module 01-Lesson 01_Intro to Natural Language Processing/10. NLP Services-vTupzLkpxJU.mp416.49MB

Part 01-Module 01-Lesson 01_Intro to Natural Language Processing/11. Getting Started with Watson-9LTS9JfGNzM.mp421.81MB

Part 01-Module 01-Lesson 01_Intro to Natural Language Processing/12. Deploying a Bluemix Application-YF2SgUXzk9k.mp42.85MB

Part 01-Module 01-Lesson 01_Intro to Natural Language Processing/13. Towards Augmented Intelligence-6y2B8VKoGTw.mp412.37MB

Part 02-Module 01-Lesson 01_Deep Neural Networks/01. Introduction-ZWRZvOXiC28.mp412.77MB

Part 02-Module 01-Lesson 01_Deep Neural Networks/02. Classsification Example-Dh625piH7Z0.mp42.07MB

Part 02-Module 01-Lesson 01_Deep Neural Networks/03. Classification Example-46PywnGa_cQ.mp41.62MB

Part 02-Module 01-Lesson 01_Deep Neural Networks/04. Linear Boundaries-X-uMlsBi07k.mp43.85MB

Part 02-Module 01-Lesson 01_Deep Neural Networks/05. 09 Higher Dimensions-eBHunImDmWw.mp42.59MB

Part 02-Module 01-Lesson 01_Deep Neural Networks/06. DL 06 Perceptron Definition Fix V2-hImSxZyRiOw.mp45.13MB

Part 02-Module 01-Lesson 01_Deep Neural Networks/07. Why Neural Networks-zAkzOZntK6Y.mp4982.27KB

Part 02-Module 01-Lesson 01_Deep Neural Networks/08. AND And OR Perceptrons-45K5N0P9wJk.mp42.68MB

Part 02-Module 01-Lesson 01_Deep Neural Networks/08. XOR Perceptron-TF83GfjYLdw.mp4947KB

Part 02-Module 01-Lesson 01_Deep Neural Networks/09. 07 Perceptron Algorithm Trick-lif_qPmXvWA.mp43.66MB

Part 02-Module 01-Lesson 01_Deep Neural Networks/09. DL 10 S Perceptron Algorithm-fATmrG2hQzI.mp4260.01KB

Part 02-Module 01-Lesson 01_Deep Neural Networks/09. Perceptron Algorithm--zhTROHtscQ.mp41.92MB

Part 02-Module 01-Lesson 01_Deep Neural Networks/10. Perceptron Agorithm Pseudocode-p8Q3yu9YqYk.mp42.87MB

Part 02-Module 01-Lesson 01_Deep Neural Networks/11. Non-Linear Regions-B8UrWnHh1Wc.mp41.33MB

Part 02-Module 01-Lesson 01_Deep Neural Networks/12. Error Functions-YfUUunxWIJw.mp43.54MB

Part 02-Module 01-Lesson 01_Deep Neural Networks/13. Error Functions-jfKShxGAbok.mp47.21MB

Part 02-Module 01-Lesson 01_Deep Neural Networks/14. Discrete vs Continuous-rdP-RPDFkl0.mp42.26MB

Part 02-Module 01-Lesson 01_Deep Neural Networks/14. Discrete vs. Continuous-Rm2KxFaPiJg.mp45.35MB

Part 02-Module 01-Lesson 01_Deep Neural Networks/15. DL 18 Q Softmax V2-RC_A9Tu99y4.mp44.01MB

Part 02-Module 01-Lesson 01_Deep Neural Networks/15. DL 18 S Softmax-n8S-v_LCTms.mp41.95MB

Part 02-Module 01-Lesson 01_Deep Neural Networks/15. Quiz - Softmax-NNoezNnAMTY.mp41.73MB

Part 02-Module 01-Lesson 01_Deep Neural Networks/16. One-Hot Encoding-AePvjhyvsBo.mp41.65MB

Part 02-Module 01-Lesson 01_Deep Neural Networks/17. Maximum Likelihood 1-1yJx-QtlvNI.mp45.75MB

Part 02-Module 01-Lesson 01_Deep Neural Networks/17. Maximum Likelihood 2-6nUUeQ9AeUA.mp43.85MB

Part 02-Module 01-Lesson 01_Deep Neural Networks/18. Quiz - Cross 1--xxrisIvD0E.mp43.02MB

Part 02-Module 01-Lesson 01_Deep Neural Networks/18. Quiz Cross Entropy-njq6bYrPqSU.mp41.86MB

Part 02-Module 01-Lesson 01_Deep Neural Networks/19. Cross Entropy 1-iREoPUrpXvE.mp44.22MB

Part 02-Module 01-Lesson 01_Deep Neural Networks/20. CrossEntropy V1-1BnhC6e0TFw.mp46.61MB

Part 02-Module 01-Lesson 01_Deep Neural Networks/20. Formula For Cross 1-qvr_ego_d6w.mp42.08MB

Part 02-Module 01-Lesson 01_Deep Neural Networks/21. DL 27 Multi-Class Cross Entropy 2 Fix-keDswcqkees.mp44.14MB

Part 02-Module 01-Lesson 01_Deep Neural Networks/22. DL 29 Logistic Regression-Minimizing The Error Function-KayqiYijlzc.mp41.49MB

Part 02-Module 01-Lesson 01_Deep Neural Networks/22. Error Function-V5kkHldUlVU.mp44.84MB

Part 02-Module 01-Lesson 01_Deep Neural Networks/23. Gradient Descent-rhVIF-nigrY.mp43.76MB

Part 02-Module 01-Lesson 01_Deep Neural Networks/24. Gradient Descent Vs Perceptron Algorithm-uL5LuRPivTA.mp43.2MB

Part 02-Module 01-Lesson 01_Deep Neural Networks/25. Continuous Perceptrons-07-JJ-aGEfM.mp41.13MB

Part 02-Module 01-Lesson 01_Deep Neural Networks/26. Non-Linear Data-F7ZiE8PQiSc.mp42.14MB

Part 02-Module 01-Lesson 01_Deep Neural Networks/27. Non-Linear Models-HWuBKCZsCo8.mp41.13MB

Part 02-Module 01-Lesson 01_Deep Neural Networks/28. 29 Neural Network Architecture 2-FWN3Sw5fFoM.mp42.83MB

Part 02-Module 01-Lesson 01_Deep Neural Networks/28. Combinando modelos-Boy3zHVrWB4.mp44.73MB

Part 02-Module 01-Lesson 01_Deep Neural Networks/28. Layers-pg99FkXYK0M.mp43.11MB

Part 02-Module 01-Lesson 01_Deep Neural Networks/28. Multiclass Classification-uNTtvxwfox0.mp41.88MB

Part 02-Module 01-Lesson 01_Deep Neural Networks/29. DL 41 Feedforward FIX V2-hVCuvMGOfyY.mp45.33MB

Part 02-Module 01-Lesson 01_Deep Neural Networks/29. DL 42 Neural Network Error Function (1)-SC1wEW7TtKs.mp41.72MB

Part 02-Module 01-Lesson 01_Deep Neural Networks/30. Backpropagation V2-1SmY3TZTyUk.mp46.52MB

Part 02-Module 01-Lesson 01_Deep Neural Networks/30. Calculating The Gradient 1 -tVuZDbUrzzI.mp43.31MB

Part 02-Module 01-Lesson 01_Deep Neural Networks/30. Chain Rule-YAhIBOnbt54.mp41.46MB

Part 02-Module 01-Lesson 01_Deep Neural Networks/30. DL 46 Calculating The Gradient 2 V2 (2)-7lidiTGIlN4.mp45.69MB

Part 02-Module 01-Lesson 01_Deep Neural Networks/34. Training Optimization-UiGKhx9pUYc.mp42.96MB

Part 02-Module 01-Lesson 01_Deep Neural Networks/35. Batch Vs Stochastic Gradient Descent-2p58rVgqsgo.mp43.95MB

Part 02-Module 01-Lesson 01_Deep Neural Networks/36. Learning Rate-TwJ8aSZoh2U.mp4927.05KB

Part 02-Module 01-Lesson 01_Deep Neural Networks/37. Testing-EeBZpb-PSac.mp42MB

Part 02-Module 01-Lesson 01_Deep Neural Networks/38. Underfitting And Overfitting-xj4PlXMsN-Y.mp46.42MB

Part 02-Module 01-Lesson 01_Deep Neural Networks/39. Model Complexity Graph-NnS0FJyVcDQ.mp44.9MB

Part 02-Module 01-Lesson 01_Deep Neural Networks/40. DL 53 Q Regularization-KxROxcRsHL8.mp41.01MB

Part 02-Module 01-Lesson 01_Deep Neural Networks/41. Regularization-ndYnUrx8xvs.mp47.57MB

Part 02-Module 01-Lesson 01_Deep Neural Networks/42. Dropout-Ty6K6YiGdBs.mp44.22MB

Part 02-Module 01-Lesson 01_Deep Neural Networks/43. Vanishing Gradient-W_JJm_5syFw.mp41.32MB

Part 02-Module 01-Lesson 01_Deep Neural Networks/44. Other Activation Functions-kA-1vUt6cvQ.mp42.3MB

Part 02-Module 01-Lesson 01_Deep Neural Networks/45. Local Minima-gF_sW_nY-xw.mp4819.86KB

Part 02-Module 01-Lesson 01_Deep Neural Networks/46. Random Restart-idyBBCzXiqg.mp4394.99KB

Part 02-Module 01-Lesson 01_Deep Neural Networks/47. Momentum-r-rYz_PEWC8.mp42.14MB

Part 02-Module 01-Lesson 01_Deep Neural Networks/49. Error Functions Around the World-34AAcTECu2A.mp41.73MB

Part 02-Module 01-Lesson 01_Deep Neural Networks/50. Keras Lab-a50un22BsLI.mp42.19MB

Part 02-Module 01-Lesson 01_Deep Neural Networks/52. Outro-HZt6bf73bOo.mp43.02MB

Part 02-Module 02-Lesson 01_Convolutional Neural Networks/01. Introducing Alexis-38ExGpdyvJI.mp42.05MB

Part 02-Module 02-Lesson 01_Convolutional Neural Networks/02. Applications of CNNs-HrYNL_1SV2Y.mp417.7MB

Part 02-Module 02-Lesson 01_Convolutional Neural Networks/03. How Computers Interpret Images-V4f6p6uRhu8.mp46.18MB

Part 02-Module 02-Lesson 01_Convolutional Neural Networks/04. MLPs For Image Classification-TIFStebu530.mp44.4MB

Part 02-Module 02-Lesson 01_Convolutional Neural Networks/05. Categorical Cross-Entropy-3sDYifgjFck.mp45.42MB

Part 02-Module 02-Lesson 01_Convolutional Neural Networks/06. Model Validation in Keras-002jNXSM6CU.mp45.2MB

Part 02-Module 02-Lesson 01_Convolutional Neural Networks/07. When do MLPs (not) work well-deMeuLdZN3Q.mp45.54MB

Part 02-Module 02-Lesson 01_Convolutional Neural Networks/09. Local Connectivity-z9wiDg0w-Dc.mp413.09MB

Part 02-Module 02-Lesson 01_Convolutional Neural Networks/10. Convolutional Layers-h5R_JvdUrUI.mp48.04MB

Part 02-Module 02-Lesson 01_Convolutional Neural Networks/11. Convolutional Layers-RnM1D-XI--8.mp419.81MB

Part 02-Module 02-Lesson 01_Convolutional Neural Networks/12. Stride and Padding-0r9o8hprDXQ.mp47.98MB

Part 02-Module 02-Lesson 01_Convolutional Neural Networks/15. Pooling Layers-OkkIZNs7Cyc.mp45.82MB

Part 02-Module 02-Lesson 01_Convolutional Neural Networks/17. CNNs For Image Classification-l9vg_1YUlzg.mp418.16MB

Part 02-Module 02-Lesson 01_Convolutional Neural Networks/18. CNNs in Keras Practical Example-faFvmGDwXX0.mp48.71MB

Part 02-Module 02-Lesson 01_Convolutional Neural Networks/20. Image Augmentation in Keras-odStujZq3GY.mp410.26MB

Part 02-Module 02-Lesson 01_Convolutional Neural Networks/22. Groundbreaking CNN Architectures-ddrB-mhMfkY.mp48.09MB

Part 02-Module 02-Lesson 01_Convolutional Neural Networks/23. Visualizing CNNs-mnqS_EhEZVg.mp49.2MB

Part 02-Module 02-Lesson 01_Convolutional Neural Networks/25. Transfer Learning-LHG5FltaR6I.mp413.32MB

Part 02-Module 02-Lesson 01_Convolutional Neural Networks/26. Transfer Learning in Keras-HsIAznMM1LA.mp412.92MB

Part 02-Module 04-Lesson 01_Recurrent Neural Networks/01. Introducing Jeremy-U7RmFpVevis.mp42.52MB

Part 02-Module 04-Lesson 01_Recurrent Neural Networks/02. Section 1 Introduction-_zo6RiwmDCk.mp44.72MB

Part 02-Module 04-Lesson 01_Recurrent Neural Networks/03. Motivation for RNNs-vPhD02WxMk8.mp45.73MB

Part 02-Module 04-Lesson 01_Recurrent Neural Networks/04. Vanilla learning and structured input-oAt0eYD5_Tc.mp45.78MB

Part 02-Module 04-Lesson 01_Recurrent Neural Networks/05. Section 2 Introduction-behe53793wo.mp41.36MB

Part 02-Module 04-Lesson 01_Recurrent Neural Networks/06. How do we model an ordered sequence-LYcB8iV2bGE.mp45.94MB

Part 02-Module 04-Lesson 01_Recurrent Neural Networks/07. Simple recursive examples-F4-CBqMsd_Y.mp47.53MB

Part 02-Module 04-Lesson 01_Recurrent Neural Networks/11. Graphical model representations of recursive sequences-OS9yQCTzCkg.mp47.63MB

Part 02-Module 04-Lesson 01_Recurrent Neural Networks/12. A simple model for my savings account balance-JQ2Nzzxx5oQ.mp49.01MB

Part 02-Module 04-Lesson 01_Recurrent Neural Networks/13. Summarizing recursivity-l1H8dfGW2A4.mp41.73MB

Part 02-Module 04-Lesson 01_Recurrent Neural Networks/14. Section 3 Introduction-VyE6NcPbX9Q.mp41.49MB

Part 02-Module 04-Lesson 01_Recurrent Neural Networks/15. AIND RNN 3 0-jXdIx18dIa0.mp42.84MB

Part 02-Module 04-Lesson 01_Recurrent Neural Networks/16. AIND RNN 3 1 1-NMZ4fU2CuHg.mp43.75MB

Part 02-Module 04-Lesson 01_Recurrent Neural Networks/17. 3 1 2 Introducing A Parameterized Formula-I72EOcAroFk.mp43.9MB

Part 02-Module 04-Lesson 01_Recurrent Neural Networks/18. AIND RNN 3 1 3-R1T3JXi_jKY.mp43.26MB

Part 02-Module 04-Lesson 01_Recurrent Neural Networks/19. AIND RNN 3 1 4-XYljYztPvUs.mp43.35MB

Part 02-Module 04-Lesson 01_Recurrent Neural Networks/20. AIND RNN 3 1 5-6LgdU4avFSk.mp42.61MB

Part 02-Module 04-Lesson 01_Recurrent Neural Networks/21. 3 2 0 Example 2-2qYjlOV4Vi0.mp41.14MB

Part 02-Module 04-Lesson 01_Recurrent Neural Networks/22. AIND RNN 3 2 1-ZFWOCob2gZ8.mp42.87MB

Part 02-Module 04-Lesson 01_Recurrent Neural Networks/23. AIND RNN 3 2 2-R4ACff0v7Vk.mp43.76MB

Part 02-Module 04-Lesson 01_Recurrent Neural Networks/24. 3 3 Twists On Example 2 (1)-Xf1oAaTd42w.mp45.36MB

Part 02-Module 04-Lesson 01_Recurrent Neural Networks/25. 3 4 Example 4-UfOUisfQPZc.mp44.46MB

Part 02-Module 04-Lesson 01_Recurrent Neural Networks/26. 3 5 Summary-imv4cLtF38o.mp41.68MB

Part 02-Module 04-Lesson 01_Recurrent Neural Networks/27. Introduction to Section 4-xx4PxKWVmHo.mp41.99MB

Part 02-Module 04-Lesson 01_Recurrent Neural Networks/29. Flaws with the FNN approach-sUXrzpAkF9A.mp47.18MB

Part 02-Module 04-Lesson 01_Recurrent Neural Networks/30. RNNs 4 2 Basic RNN Derivation-Y3-YuSbhbQM.mp48.65MB

Part 02-Module 04-Lesson 01_Recurrent Neural Networks/31. RNNs 4 3 Formulating A Least Squares Loss-F5PVwVrEVHY.mp43.43MB

Part 02-Module 04-Lesson 01_Recurrent Neural Networks/32. RNNs 4 4 RNN Properties- Memory-0B8O2eNv2DY.mp44.41MB

Part 02-Module 04-Lesson 01_Recurrent Neural Networks/33. RNNs 4 5 RNN Properties- Graphical Models-LON9wniFUiE.mp42.24MB

Part 02-Module 04-Lesson 01_Recurrent Neural Networks/34. Technical Issues-6Bpu_XydW2k.mp41.88MB

Part 02-Module 04-Lesson 01_Recurrent Neural Networks/35. Section & Course Summary-gYCL4RBvzRM.mp43.02MB

Part 02-Module 04-Lesson 01_Recurrent Neural Networks/36. Outro-LurBj_gmFwk.mp42.43MB

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

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

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

Part 02-Module 04-Lesson 02_Long Short-Term Memory Networks (LSTM)/05. Learn Gate-aVHVI7ovbHY.mp42.22MB

Part 02-Module 04-Lesson 02_Long Short-Term Memory Networks (LSTM)/06. Forget Gate-iWxpfxLUPSU.mp41.04MB

Part 02-Module 04-Lesson 02_Long Short-Term Memory Networks (LSTM)/07. Remember Gate-0qlm86HaXuU.mp4676.91KB

Part 02-Module 04-Lesson 02_Long Short-Term Memory Networks (LSTM)/08. LSTM 7 Use Gate-5Ifolm1jTdY.mp41.5MB

Part 02-Module 04-Lesson 02_Long Short-Term Memory Networks (LSTM)/09. Putting It All Together-IF8FlKW-Zo0.mp41.58MB

Part 02-Module 04-Lesson 02_Long Short-Term Memory Networks (LSTM)/11. Other Architectures-MsxFDuYlTuQ.mp41.71MB

Part 02-Module 04-Lesson 03_Implementing RNNs and LSTMs/02. IntroToRNNs Render-64HSG6HAfEI.mp43.99MB

Part 02-Module 04-Lesson 03_Implementing RNNs and LSTMs/03. LSTMs-RYbSHogZetc.mp46.87MB

Part 02-Module 04-Lesson 03_Implementing RNNs and LSTMs/04. Character-Wise RNN-dXl3eWCGLdU.mp42.88MB

Part 02-Module 04-Lesson 03_Implementing RNNs and LSTMs/05. Sequence-Batching-Z4OiyU0Cldg.mp42.29MB

Part 02-Module 04-Lesson 03_Implementing RNNs and LSTMs/07. Implementing a Character-wise RNN-KPCMn_jg2oY.mp413.63MB

Part 02-Module 04-Lesson 03_Implementing RNNs and LSTMs/08. Batching Data Solution-o3nBxHJLQcc.mp45.08MB

Part 02-Module 04-Lesson 03_Implementing RNNs and LSTMs/09. LSTM Cell-ajC-5uWB8S4.mp47.79MB

Part 02-Module 04-Lesson 03_Implementing RNNs and LSTMs/10. LSTM Cell Solution-X4uA0dq_4jA.mp43.55MB

Part 02-Module 04-Lesson 03_Implementing RNNs and LSTMs/11. RNN Output-RkanDkcrTxs.mp48.92MB

Part 02-Module 04-Lesson 03_Implementing RNNs and LSTMs/12. Network Loss-itu-uNK4brc.mp44.28MB

Part 02-Module 04-Lesson 03_Implementing RNNs and LSTMs/13. Output And Loss Solutions-CT8hcU7FmGc.mp44.69MB

Part 02-Module 04-Lesson 03_Implementing RNNs and LSTMs/14. Build The Network-RVNjDlWTBQU.mp47.1MB

Part 02-Module 04-Lesson 03_Implementing RNNs and LSTMs/15. Build The Network And Results-hu8iMMqajmQ.mp413.27MB

Part 02-Module 04-Lesson 04_Hyperparameters/02. Introduction-erwnzFD7AeE.mp42.22MB

Part 02-Module 04-Lesson 04_Hyperparameters/03. Learning Rate-HLMjeDez7ps.mp49.62MB

Part 02-Module 04-Lesson 04_Hyperparameters/05. Minibatch Size-GrrO1NFxaW8.mp44.78MB

Part 02-Module 04-Lesson 04_Hyperparameters/06. Number Of Iterations-TTdHpSb4DV8.mp41.46MB

Part 02-Module 04-Lesson 04_Hyperparameters/07. Number Of Hidden Units Layers-IkGAIQH5wH8.mp43.4MB

Part 02-Module 04-Lesson 04_Hyperparameters/08. RNN Hyperparameters-yQvnv7l_aUo.mp44.12MB

Part 02-Module 04-Lesson 05_Sentiment Prediction with RNN/02. Sentiment Prediction-uGN3rZJRiMY.mp411.25MB

Part 02-Module 04-Lesson 05_Sentiment Prediction with RNN/03. Data Preprocessing-h4-LwZU9_k8.mp46.86MB

Part 02-Module 04-Lesson 05_Sentiment Prediction with RNN/04. Creating Testing Sets-BRBbrNLz1ho.mp42.13MB

Part 02-Module 04-Lesson 05_Sentiment Prediction with RNN/05. Building The RNN 1-XTD6slf64fM.mp419.11MB

Part 02-Module 04-Lesson 05_Sentiment Prediction with RNN/06. Training The Network-nknJ3Xu3ld0.mp48.41MB

Part 02-Module 04-Lesson 05_Sentiment Prediction with RNN/07. Sentiment RNN 2-V9YGGjmoHS0.mp423.11MB

Part 03-Module 01-Lesson 01_Natural Language Processing/01. Natural Language Processing-UQBxJzoCp-I.mp43.39MB

Part 03-Module 01-Lesson 01_Natural Language Processing/02. NLP M1-L1 01 NLP Pipeline-vJx6oKlu_MM.mp41.28MB

Part 03-Module 01-Lesson 01_Natural Language Processing/03. Text Processing-pqheVyctkNQ.mp42.96MB

Part 03-Module 01-Lesson 01_Natural Language Processing/04. Feature Extraction-UgENzCmfFWE.mp43.47MB

Part 03-Module 01-Lesson 01_Natural Language Processing/05. Modeling-P4w_2rkxBvE.mp41.19MB

Part 03-Module 01-Lesson 02_Text Processing/01. Text Processing-6LO6I5M18PQ.mp41.77MB

Part 03-Module 01-Lesson 02_Text Processing/03. Capturing Text Data-Z4mnMN1ApG4.mp42.37MB

Part 03-Module 01-Lesson 02_Text Processing/05. Cleaning-qawXp9DPV6I.mp419.59MB

Part 03-Module 01-Lesson 02_Text Processing/06. Normalization-eOV2UUY8vtM.mp43.13MB

Part 03-Module 01-Lesson 02_Text Processing/07. Tokenization-4Ieotbeh4u8.mp43.22MB

Part 03-Module 01-Lesson 02_Text Processing/09. Stop Word Removal-WAU_Ij0GJbw.mp41.96MB

Part 03-Module 01-Lesson 02_Text Processing/10. Part-of-Speech Tagging-WFEu8bXI5OA.mp42.15MB

Part 03-Module 01-Lesson 02_Text Processing/11. Named Entity Recognition-QUQu2nsE7vE.mp41.17MB

Part 03-Module 01-Lesson 02_Text Processing/12. Stemming And Lemmatization-7Gjf81u5hmw.mp44.93MB

Part 03-Module 01-Lesson 02_Text Processing/13. Summary-zKYEvRd2XmI.mp4977.95KB

Part 04-Module 01-Lesson 01_Feature Extraction/01. Feature Extraction-Bd6TJB8eVLQ.mp42.26MB

Part 04-Module 01-Lesson 01_Feature Extraction/02. Bag Of Words-A7M1z8yLl0w.mp44.01MB

Part 04-Module 01-Lesson 01_Feature Extraction/03. TF-IDF-XZBiBIRcACE.mp42.05MB

Part 04-Module 01-Lesson 01_Feature Extraction/04. One-Hot Encoding-a0j1CDXFYZI.mp41.08MB

Part 04-Module 01-Lesson 01_Feature Extraction/05. Word Embeddings-4mM_S9L2_JQ.mp41.22MB

Part 04-Module 01-Lesson 01_Feature Extraction/06. Word2Vec-7jjappzGRe0.mp42.98MB

Part 04-Module 01-Lesson 01_Feature Extraction/07. GloVe-KK3PMIiIn8o.mp43.81MB

Part 04-Module 01-Lesson 01_Feature Extraction/08. Embeddings For Deep Learning-gj8u1KG0H2w.mp44.7MB

Part 04-Module 01-Lesson 01_Feature Extraction/09. T-SNE-xxcK8oZ6_WE.mp45.56MB

Part 05-Module 01-Lesson 01_Modeling/01. AIND NLP L2 HS 04 Modeling V2-RGrGi-eKhOQ.mp42.86MB

Part 05-Module 01-Lesson 01_Modeling/08. NLP Summary-B9ul8fsQYOA.mp41.38MB

Part 06-Module 01-Lesson 01_Embeddings and Word2Vec/03. Implementing Word2Vec-7M431_f9HgE.mp423.33MB

Part 06-Module 01-Lesson 01_Embeddings and Word2Vec/04. Subsampling Solution-MAUM_mV_lj8.mp49.65MB

Part 06-Module 01-Lesson 01_Embeddings and Word2Vec/05. Making Batches-jx7qwdw-94k.mp47.73MB

Part 06-Module 01-Lesson 01_Embeddings and Word2Vec/06. Batches Solution-DdfR0RjSC-Q.mp43.88MB

Part 06-Module 01-Lesson 01_Embeddings and Word2Vec/07. Building The Network-fhSb5c6UX6M.mp48.09MB

Part 06-Module 01-Lesson 01_Embeddings and Word2Vec/08. Negative Sampling-gW17AHBKbHY.mp44.16MB

Part 06-Module 01-Lesson 01_Embeddings and Word2Vec/09. Building The Network Solution-pkBAhQ2Ki-8.mp47.34MB

Part 06-Module 01-Lesson 01_Embeddings and Word2Vec/10. Training Results-uISA5ns47s8.mp49.78MB

Part 06-Module 01-Lesson 02_Sequence to Sequence/02. Jay's Introduction-HPOzAlXhuxQ.mp45.81MB

Part 06-Module 01-Lesson 02_Sequence to Sequence/03. Applications seq2seq-tDJBDwriJYQ.mp42.48MB

Part 06-Module 01-Lesson 02_Sequence to Sequence/04. Architecture encoder decoder-dkHdEAJnV_w.mp44.49MB

Part 06-Module 01-Lesson 02_Sequence to Sequence/05. Architecture in More Depth-rdAo4MqLbEk.mp45.35MB

Part 06-Module 01-Lesson 02_Sequence to Sequence/06. Preprocessing-ktQW6p9pOS4.mp48.88MB