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Udemy Machine Learning Data Science and Generative AI with Pyt

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Files:
  1. [CourseClub.Me].url 122 bytes
  2. [GigaCourse.Com].url 49 bytes
  3. 001 Introduction.mp4 59.6 MB
  4. 001 Introduction_en.srt 6.1 KB
  5. 002 Udemy 101 Getting the Most From This Course.mp4 17.4 MB
  6. 002 Udemy 101 Getting the Most From This Course_en.srt 4.9 KB
  7. 003 Important note.html 575 bytes
  8. 004 Installation Getting Started.html 1.2 KB
  9. 005 [Activity] WINDOWS Installing and Using Anaconda & Course Materials.mp4 102.0 MB
  10. 005 [Activity] WINDOWS Installing and Using Anaconda & Course Materials_en.srt 20.7 KB
  11. 006 [Activity] MAC Installing and Using Anaconda & Course Materials.mp4 96.2 MB
  12. 006 [Activity] MAC Installing and Using Anaconda & Course Materials_en.srt 16.9 KB
  13. 007 [Activity] LINUX Installing and Using Anaconda & Course Materials.mp4 85.5 MB
  14. 007 [Activity] LINUX Installing and Using Anaconda & Course Materials_en.srt 18.0 KB
  15. 008 Python Basics, Part 1 [Optional].mp4 26.9 MB
  16. 008 Python Basics, Part 1 [Optional]_en.srt 9.5 KB
  17. 009 [Activity] Python Basics, Part 2 [Optional].mp4 20.6 MB
  18. 009 [Activity] Python Basics, Part 2 [Optional]_en.srt 9.3 KB
  19. 010 [Activity] Python Basics, Part 3 [Optional].mp4 5.1 MB
  20. 010 [Activity] Python Basics, Part 3 [Optional]_en.srt 5.2 KB
  21. 011 [Activity] Python Basics, Part 4 [Optional].mp4 8.2 MB
  22. 011 [Activity] Python Basics, Part 4 [Optional]_en.srt 7.1 KB
  23. 012 Introducing the Pandas Library [Optional].mp4 44.2 MB
  24. 012 Introducing the Pandas Library [Optional]_en.srt 21.9 KB
  25. 001 Types of Data (Numerical, Categorical, Ordinal).mp4 73.1 MB
  26. 001 Types of Data (Numerical, Categorical, Ordinal)_en.srt 14.4 KB
  27. 002 Mean, Median, Mode.mp4 16.0 MB
  28. 002 Mean, Median, Mode_en.srt 11.6 KB
  29. 003 [Activity] Using mean, median, and mode in Python.mp4 44.5 MB
  30. 003 [Activity] Using mean, median, and mode in Python_en.srt 19.3 KB
  31. 004 [Activity] Variation and Standard Deviation.mp4 103.4 MB
  32. 004 [Activity] Variation and Standard Deviation_en.srt 23.0 KB
  33. 005 Probability Density Function; Probability Mass Function.mp4 6.9 MB
  34. 005 Probability Density Function; Probability Mass Function_en.srt 7.1 KB
  35. 006 Common Data Distributions (Normal, Binomial, Poisson, etc).mp4 28.3 MB
  36. 006 Common Data Distributions (Normal, Binomial, Poisson, etc)_en.srt 14.5 KB
  37. 007 [Activity] Percentiles and Moments.mp4 42.6 MB
  38. 007 [Activity] Percentiles and Moments_en.srt 26.8 KB
  39. 008 [Activity] A Crash Course in matplotlib.mp4 78.7 MB
  40. 008 [Activity] A Crash Course in matplotlib_en.srt 26.1 KB
  41. 009 [Activity] Advanced Visualization with Seaborn.mp4 96.1 MB
  42. 009 [Activity] Advanced Visualization with Seaborn_en.srt 35.7 KB
  43. 010 [Activity] Covariance and Correlation.mp4 69.5 MB
  44. 010 [Activity] Covariance and Correlation_en.srt 23.7 KB
  45. 011 [Exercise] Conditional Probability.mp4 94.0 MB
  46. 011 [Exercise] Conditional Probability_en.srt 34.1 KB
  47. 012 Exercise Solution Conditional Probability of Purchase by Age.mp4 15.0 MB
  48. 012 Exercise Solution Conditional Probability of Purchase by Age_en.srt 4.8 KB
  49. 013 Bayes' Theorem.mp4 56.1 MB
  50. 013 Bayes' Theorem_en.srt 10.4 KB
  51. 001 [Activity] Linear Regression.mp4 93.0 MB
  52. 001 [Activity] Linear Regression_en.srt 23.8 KB
  53. 002 [Activity] Polynomial Regression.mp4 60.5 MB
  54. 002 [Activity] Polynomial Regression_en.srt 15.7 KB
  55. 003 [Activity] Multiple Regression, and Predicting Car Prices.mp4 94.1 MB
  56. 003 [Activity] Multiple Regression, and Predicting Car Prices_en.srt 34.2 KB
  57. 004 Multi-Level Models.mp4 27.2 MB
  58. 004 Multi-Level Models_en.srt 9.8 KB
  59. [CourseClub.Me].url 122 bytes
  60. [GigaCourse.Com].url 49 bytes
  61. 001 Supervised vs. Unsupervised Learning, and TrainTest.mp4 56.7 MB
  62. 001 Supervised vs. Unsupervised Learning, and TrainTest_en.srt 19.4 KB
  63. 002 [Activity] Using TrainTest to Prevent Overfitting a Polynomial Regression.mp4 21.6 MB
  64. 002 [Activity] Using TrainTest to Prevent Overfitting a Polynomial Regression_en.srt 11.9 KB
  65. 003 Bayesian Methods Concepts.mp4 9.8 MB
  66. 003 Bayesian Methods Concepts_en.srt 8.1 KB
  67. 004 [Activity] Implementing a Spam Classifier with Naive Bayes.mp4 81.4 MB
  68. 004 [Activity] Implementing a Spam Classifier with Naive Bayes_en.srt 16.6 KB
  69. 005 K-Means Clustering.mp4 26.0 MB
  70. 005 K-Means Clustering_en.srt 15.6 KB
  71. 006 [Activity] Clustering people based on income and age.mp4 22.0 MB
  72. 006 [Activity] Clustering people based on income and age_en.srt 11.1 KB
  73. 007 Measuring Entropy.mp4 12.1 MB
  74. 007 Measuring Entropy_en.srt 6.4 KB
  75. 008 [Activity] WINDOWS Installing Graphviz.mp4 949.3 KB
  76. 008 [Activity] WINDOWS Installing Graphviz_en.srt 872 bytes
  77. 009 [Activity] MAC Installing Graphviz.mp4 9.1 MB
  78. 009 [Activity] MAC Installing Graphviz_en.srt 1.8 KB
  79. 010 [Activity] LINUX Installing Graphviz.mp4 2.5 MB
  80. 010 [Activity] LINUX Installing Graphviz_en.srt 1.4 KB
  81. 011 Decision Trees Concepts.mp4 81.5 MB
  82. 011 Decision Trees Concepts_en.srt 18.7 KB
  83. 012 [Activity] Decision Trees Predicting Hiring Decisions.mp4 57.8 MB
  84. 012 [Activity] Decision Trees Predicting Hiring Decisions_en.srt 20.1 KB
  85. 013 Ensemble Learning.mp4 37.0 MB
  86. 013 Ensemble Learning_en.srt 12.7 KB
  87. 014 [Activity] XGBoost.mp4 79.3 MB
  88. 014 [Activity] XGBoost_en.srt 33.7 KB
  89. 015 Support Vector Machines (SVM) Overview.mp4 16.3 MB
  90. 015 Support Vector Machines (SVM) Overview_en.srt 9.5 KB
  91. 016 [Activity] Using SVM to cluster people using scikit-learn.mp4 38.5 MB
  92. 016 [Activity] Using SVM to cluster people using scikit-learn_en.srt 20.0 KB
  93. 001 User-Based Collaborative Filtering.mp4 81.7 MB
  94. 001 User-Based Collaborative Filtering_en.srt 17.3 KB
  95. 002 Item-Based Collaborative Filtering.mp4 23.2 MB
  96. 002 Item-Based Collaborative Filtering_en.srt 17.8 KB
  97. 003 [Activity] Finding Movie Similarities using Cosine Similarity.mp4 82.7 MB
  98. 003 [Activity] Finding Movie Similarities using Cosine Similarity_en.srt 17.9 KB
  99. 004 [Activity] Improving the Results of Movie Similarities.mp4 56.1 MB
  100. 004 [Activity] Improving the Results of Movie Similarities_en.srt 16.2 KB
  101. 005 [Activity] Making Movie Recommendations with Item-Based Collaborative Filtering.mp4 124.1 MB
  102. 005 [Activity] Making Movie Recommendations with Item-Based Collaborative Filtering_en.srt 20.3 KB
  103. 006 [Exercise] Improve the recommender's results.mp4 28.0 MB
  104. 006 [Exercise] Improve the recommender's results_en.srt 12.1 KB
  105. 001 K-Nearest-Neighbors Concepts.mp4 14.0 MB
  106. 001 K-Nearest-Neighbors Concepts_en.srt 7.9 KB
  107. 002 [Activity] Using KNN to predict a rating for a movie.mp4 85.5 MB
  108. 002 [Activity] Using KNN to predict a rating for a movie_en.srt 24.1 KB
  109. 003 Dimensionality Reduction; Principal Component Analysis (PCA).mp4 38.1 MB
  110. 003 Dimensionality Reduction; Principal Component Analysis (PCA)_en.srt 11.7 KB
  111. 004 [Activity] PCA Example with the Iris data set.mp4 65.8 MB
  112. 004 [Activity] PCA Example with the Iris data set_en.srt 17.9 KB
  113. 005 Data Warehousing Overview ETL and ELT.mp4 58.7 MB
  114. 005 Data Warehousing Overview ETL and ELT_en.srt 18.1 KB
  115. 006 Cat-and-Mouse-Example.url 103 bytes
  116. 006 Pac-Man-Example.url 108 bytes
  117. 006 Python-Markov-Decision-Process-Toolbox.url 82 bytes
  118. 006 Reinforcement Learning.mp4 125.2 MB
  119. 006 Reinforcement Learning_en.srt 25.3 KB
  120. 007 [Activity] Reinforcement Learning & Q-Learning with Gym.mp4 62.8 MB
  121. 007 [Activity] Reinforcement Learning & Q-Learning with Gym_en.srt 26.6 KB
  122. 008 Understanding a Confusion Matrix.mp4 7.4 MB
  123. 008 Understanding a Confusion Matrix_en.srt 11.6 KB
  124. 009 Measuring Classifiers (Precision, Recall, F1, ROC, AUC).mp4 11.7 MB
  125. 009 Measuring Classifiers (Precision, Recall, F1, ROC, AUC)_en.srt 12.7 KB
  126. external-links.txt 325 bytes
  127. 001 BiasVariance Tradeoff.mp4 23.6 MB
  128. 001 BiasVariance Tradeoff_en.srt 12.8 KB
  129. 002 [Activity] K-Fold Cross-Validation to avoid overfitting.mp4 56.9 MB
  130. 002 [Activity] K-Fold Cross-Validation to avoid overfitting_en.srt 20.6 KB
  131. 003 Data Cleaning and Normalization.mp4 73.1 MB
  132. 003 Data Cleaning and Normalization_en.srt 16.2 KB
  133. 004 [Activity] Cleaning web log data.mp4 31.0 MB
  134. 004 [Activity] Cleaning web log data_en.srt 21.8 KB
  135. 005 Normalizing numerical data.mp4 10.3 MB
  136. 005 Normalizing numerical data_en.srt 7.2 KB
  137. 006 [Activity] Detecting outliers.mp4 27.2 MB
  138. 006 [Activity] Detecting outliers_en.srt 13.3 KB
  139. 007 Feature Engineering and the Curse of Dimensionality.mp4 14.6 MB
  140. 007 Feature Engineering and the Curse of Dimensionality_en.srt 13.9 KB
  141. 008 Imputation Techniques for Missing Data.mp4 18.2 MB
  142. 008 Imputation Techniques for Missing Data_en.srt 17.3 KB
  143. 009 Handling Unbalanced Data Oversampling, Undersampling, and SMOTE.mp4 17.4 MB
  144. 009 Handling Unbalanced Data Oversampling, Undersampling, and SMOTE_en.srt 11.8 KB
  145. 010 Binning, Transforming, Encoding, Scaling, and Shuffling.mp4 42.7 MB
  146. 010 Binning, Transforming, Encoding, Scaling, and Shuffling_en.srt 16.9 KB
  147. 001 Warning about Java 21+ and Spark 3!.html 389 bytes
  148. 002 Spark installation notes for MacOS and Linux users.html 3.1 KB
  149. 003 [Activity] Installing Spark.mp4 141.4 MB
  150. 003 [Activity] Installing Spark_en.srt 21.3 KB
  151. 004 Spark Introduction.mp4 25.0 MB
  152. 004 Spark Introduction_en.srt 19.2 KB
  153. 005 Spark and the Resilient Distributed Dataset (RDD).mp4 22.3 MB
  154. 005 Spark and the Resilient Distributed Dataset (RDD)_en.srt 24.2 KB
  155. 006 Introducing MLLib.mp4 14.7 MB
  156. 006 Introducing MLLib_en.srt 10.4 KB
  157. 007 Introduction to Decision Trees in Spark.mp4 134.0 MB
  158. 007 Introduction to Decision Trees in Spark_en.srt 33.1 KB
  159. 008 [Activity] K-Means Clustering in Spark.mp4 116.1 MB
  160. 008 [Activity] K-Means Clustering in Spark_en.srt 21.1 KB
  161. 009 TF IDF.mp4 65.7 MB
  162. 009 TF IDF_en.srt 13.4 KB
  163. 010 [Activity] Searching Wikipedia with Spark.mp4 84.0 MB
  164. 010 [Activity] Searching Wikipedia with Spark_en.srt 15.6 KB
  165. 011 [Activity] Using the Spark DataFrame API for MLLib.mp4 65.1 MB
  166. 011 [Activity] Using the Spark DataFrame API for MLLib_en.srt 15.1 KB
  167. 001 Deploying Models to Real-Time Systems.mp4 17.2 MB
  168. 001 Deploying Models to Real-Time Systems_en.srt 18.8 KB
  169. 002 AB Testing Concepts.mp4 32.0 MB
  170. 002 AB Testing Concepts_en.srt 18.7 KB
  171. 003 T-Tests and P-Values.mp4 14.1 MB
  172. 003 T-Tests and P-Values_en.srt 12.3 KB
  173. 004 [Activity] Hands-on With T-Tests.mp4 47.8 MB
  174. 004 [Activity] Hands-on With T-Tests_en.srt 12.3 KB
  175. 005 Determining How Long to Run an Experiment.mp4 9.7 MB
  176. 005 Determining How Long to Run an Experiment_en.srt 7.7 KB
  177. 006 AB Test Gotchas.mp4 91.7 MB
  178. 006 AB Test Gotchas_en.srt 20.9 KB
  179. [CourseClub.Me].url 122 bytes
  180. [GigaCourse.Com].url 49 bytes
  181. 001 Deep Learning Pre-Requisites.mp4 70.4 MB
  182. 001 Deep Learning Pre-Requisites_en.srt 26.0 KB
  183. 002 The History of Artificial Neural Networks.mp4 68.9 MB
  184. 002 The History of Artificial Neural Networks_en.srt 24.2 KB
  185. 003 [Activity] Deep Learning in the Tensorflow Playground.mp4 55.7 MB
  186. 003 [Activity] Deep Learning in the Tensorflow Playground_en.srt 24.0 KB
  187. 004 Deep Learning Details.mp4 30.9 MB
  188. 004 Deep Learning Details_en.srt 20.9 KB
  189. 005 Introducing Tensorflow.mp4 46.6 MB
  190. 005 Introducing Tensorflow_en.srt 26.6 KB
  191. 006 [Activity] Using Tensorflow, Part 1.mp4 107.7 MB
  192. 006 [Activity] Using Tensorflow, Part 1_en.srt 27.7 KB
  193. 007 [Activity] Using Tensorflow, Part 2.mp4 95.1 MB
  194. 007 [Activity] Using Tensorflow, Part 2_en.srt 24.9 KB
  195. 008 [Activity] Introducing Keras.mp4 72.0 MB
  196. 008 [Activity] Introducing Keras_en.srt 28.6 KB
  197. 009 [Activity] Using Keras to Predict Political Affiliations.mp4 88.9 MB
  198. 009 [Activity] Using Keras to Predict Political Affiliations_en.srt 25.4 KB
  199. 010 Convolutional Neural Networks (CNN's).mp4 58.7 MB
  200. 010 Convolutional Neural Networks (CNN's)_en.srt 24.9 KB
  201. 011 [Activity] Using CNN's for handwriting recognition.mp4 52.8 MB
  202. 011 [Activity] Using CNN's for handwriting recognition_en.srt 16.8 KB
  203. 012 Recurrent Neural Networks (RNN's).mp4 32.8 MB
  204. 012 Recurrent Neural Networks (RNN's)_en.srt 23.0 KB
  205. 013 [Activity] Using a RNN for sentiment analysis.mp4 73.6 MB
  206. 013 [Activity] Using a RNN for sentiment analysis_en.srt 20.7 KB
  207. 014 [Activity] Transfer Learning.mp4 111.0 MB
  208. 014 [Activity] Transfer Learning_en.srt 25.3 KB
  209. 015 Tuning Neural Networks Learning Rate and Batch Size Hyperparameters.mp4 8.5 MB
  210. 015 Tuning Neural Networks Learning Rate and Batch Size Hyperparameters_en.srt 10.3 KB
  211. 016 Deep Learning Regularization with Dropout and Early Stopping.mp4 19.8 MB
  212. 016 Deep Learning Regularization with Dropout and Early Stopping_en.srt 13.9 KB
  213. 017 The Ethics of Deep Learning.mp4 120.5 MB
  214. 017 The Ethics of Deep Learning_en.srt 24.9 KB
  215. 001 Variational Auto-Encoders (VAE's) - how they work.mp4 42.9 MB
  216. 001 Variational Auto-Encoders (VAE's) - how they work_en.srt 21.6 KB
  217. 002 Variational Auto-Encoders (VAE) - Hands-on with Fashion MNIST.mp4 148.8 MB
  218. 002 Variational Auto-Encoders (VAE) - Hands-on with Fashion MNIST_en.srt 54.6 KB
  219. 002 VariationalAutoEncoders.ipynb 1.3 MB
  220. 003 Generative Adversarial Networks (GAN's) - How they work.mp4 15.2 MB
  221. 003 Generative Adversarial Networks (GAN's) - How they work_en.srt 15.9 KB
  222. 004 Generative Adversarial Networks (GAN's) - Playing with some demos.mp4 86.1 MB
  223. 004 Generative Adversarial Networks (GAN's) - Playing with some demos_en.srt 21.7 KB
  224. 005 GAN-on-Fashion-MNIST.ipynb 3.7 MB
  225. 005 Generative Adversarial Networks (GAN's) - Hands-on with Fashion MNIST.mp4 126.1 MB
  226. 005 Generative Adversarial Networks (GAN's) - Hands-on with Fashion MNIST_en.srt 32.6 KB
  227. 006 Learning More about Deep Learning.mp4 20.2 MB
  228. 006 Learning More about Deep Learning_en.srt 3.8 KB
  229. 001 The Transformer Architecture (encoders, decoders, and self-attention.).mp4 44.2 MB
  230. 001 The Transformer Architecture (encoders, decoders, and self-attention.)_en.srt 22.3 KB
  231. 002 Self-Attention, Masked Self-Attention, and Multi-Headed Self Attention in depth.mp4 41.5 MB
  232. 002 Self-Attention, Masked Self-Attention, and Multi-Headed Self Attention in depth_en.srt 21.7 KB
  233. 003 Applications of Transformers (GPT).mp4 20.2 MB
  234. 003 Applications of Transformers (GPT)_en.srt 10.1 KB
  235. 004 How GPT Works, Part 1 The GPT Transformer Architecture.mp4 30.3 MB
  236. 004 How GPT Works, Part 1 The GPT Transformer Architecture_en.srt 16.0 KB
  237. 005 How GPT Works, Part 2 Tokenization, Positional Encoding, Embedding.mp4 28.5 MB
  238. 005 How GPT Works, Part 2 Tokenization, Positional Encoding, Embedding_en.srt 10.8 KB
  239. 006 Fine Tuning Transfer Learning with Transformers.mp4 11.5 MB
  240. 006 Fine Tuning Transfer Learning with Transformers_en.srt 5.5 KB
  241. 007 Transformers-MLCourse.ipynb 6.7 MB
  242. 007 [Activity] Tokenization with Google CoLab and HuggingFace.mp4 79.0 MB
  243. 007 [Activity] Tokenization with Google CoLab and HuggingFace_en.srt 18.6 KB
  244. 008 [Activity] Positional Encoding.mp4 16.0 MB
  245. 008 [Activity] Positional Encoding_en.srt 4.3 KB
  246. 009 [Activity] Masked, Multi-Headed Self Attention with BERT, BERTViz, and exBERT.mp4 39.8 MB
  247. 009 [Activity] Masked, Multi-Headed Self Attention with BERT, BERTViz, and exBERT_en.srt 12.8 KB
  248. 010 [Activity] Using small and large GPT models within Google CoLab and HuggingFace.mp4 69.3 MB
  249. 010 [Activity] Using small and large GPT models within Google CoLab and HuggingFace_en.srt 10.8 KB
  250. 011 [Activity] Fine Tuning GPT with the IMDb dataset.mp4 85.2 MB
  251. 011 [Activity] Fine Tuning GPT with the IMDb dataset_en.srt 13.4 KB
  252. 012 From GPT to ChatGPT Deep Reinforcement Learning, Proximal Policy Gradients.mp4 51.1 MB
  253. 012 From GPT to ChatGPT Deep Reinforcement Learning, Proximal Policy Gradients_en.srt 15.9 KB
  254. 013 From GPT to ChatGPT Reinforcement Learning from Human Feedback and Moderation.mp4 37.8 MB
  255. 013 From GPT to ChatGPT Reinforcement Learning from Human Feedback and Moderation_en.srt 12.8 KB
  256. 001 Chat-Completions.py 1.2 KB
  257. 001 [Activity] The OpenAI Chat Completions API.mp4 70.4 MB
  258. 001 [Activity] The OpenAI Chat Completions API_en.srt 24.9 KB
  259. 002 Functions.py 3.5 KB
  260. 002 [Activity] Using Tools and Functions in the OpenAI Chat Completion API.mp4 61.2 MB
  261. 002 [Activity] Using Tools and Functions in the OpenAI Chat Completion API_en.srt 19.1 KB
  262. 003 Image.py 664 bytes
  263. 003 [Activity] The Images (DALL-E) API in OpenAI.mp4 29.6 MB
  264. 003 [Activity] The Images (DALL-E) API in OpenAI_en.srt 8.8 KB
  265. 004 Embedding.py 964 bytes
  266. 004 [Activity] The Embeddings API in OpenAI Finding similarities between words.mp4 32.9 MB
  267. 004 [Activity] The Embeddings API in OpenAI Finding similarities between words_en.srt 13.3 KB
  268. 005 The Legacy Fine-Tuning API for GPT Models in OpenAI.mp4 29.4 MB
  269. 005 The Legacy Fine-Tuning API for GPT Models in OpenAI_en.srt 11.5 KB
  270. 006 [Demo] Fine-Tuning OpenAI's Davinci Model to simulate Data from Star Trek.mp4 170.8 MB
  271. 006 [Demo] Fine-Tuning OpenAI's Davinci Model to simulate Data from Star Trek_en.srt 35.3 KB
  272. 006 extract-script.py 1.9 KB
  273. 007 MakingData.ipynb 13.6 KB
  274. 007 The New OpenAI Fine-Tuning API; Fine-Tuning GPT-3.5 to simulate Commander Data!.mp4 319.0 MB
  275. 007 The New OpenAI Fine-Tuning API; Fine-Tuning GPT-3.5 to simulate Commander Data!_en.srt 45.9 KB
  276. 008 Moderation.py 166 bytes
  277. 008 [Activity] The OpenAI Moderation API.mp4 17.1 MB
  278. 009 Audio.py 445 bytes
  279. 009 [Activity] The OpenAI Audio API (speech to text).mp4 28.7 MB
  280. 009 [Activity] The OpenAI Audio API (speech to text)_en.srt 8.2 KB
  281. 001 Retrieval Augmented Generation (RAG) How it works, with some examples.mp4 92.9 MB
  282. 001 Retrieval Augmented Generation (RAG) How it works, with some examples_en.srt 37.2 KB
  283. 002 Data-RAG.ipynb 100.4 KB
  284. 002 Demo Using Retrieval Augmented Generation (RAG) to simulate Data from Star Trek.mp4 184.5 MB
  285. 002 Demo Using Retrieval Augmented Generation (RAG) to simulate Data from Star Trek_en.srt 40.7 KB
  286. 001 Your final project assignment Mammogram Classification.mp4 51.6 MB
  287. 001 Your final project assignment Mammogram Classification_en.srt 14.3 KB
  288. 002 Final project review.mp4 64.5 MB
  289. 002 Final project review_en.srt 22.3 KB
  290. [CourseClub.Me].url 122 bytes
  291. [GigaCourse.Com].url 49 bytes
  292. 001 More to Explore.mp4 34.0 MB
  293. 001 More to Explore_en.srt 6.8 KB
  294. 002 Don't Forget to Leave a Rating!.html 564 bytes
  295. 003 Bonus Lecture.html 9.2 KB
  296. [CourseClub.Me].url 122 bytes
  297. [GigaCourse.Com].url 49 bytes

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