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GetFreeCourses.Co-Udemy-Complete Tensorflow 2 and Keras Deep Learning Bootcamp

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文件列表

  1. 1. Course Overview, Installs, and Setup/3. Course Setup and Installation.mp4 152MB
  2. 13. Deployment/7. Flask Front End.mp4 150MB
  3. 9. Recurrent Neural Networks - RNNs/14. Bonus - Multivariate Time Series - RNN and LSTMs.mp4 149MB
  4. 9. Recurrent Neural Networks - RNNs/13. RNN Exercise - Solutions.mp4 148MB
  5. 7. Basic Artificial Neural Networks - ANNs/27. Tensorboard.mp4 144MB
  6. 7. Basic Artificial Neural Networks - ANNs/20. Keras Project Solutions - Exploratory Data Analysis.mp4 144MB
  7. 7. Basic Artificial Neural Networks - ANNs/12. Keras Regression Code Along - Exploratory Data Analysis.mp4 137MB
  8. 12. Generative Adversarial Networks/4. Creating a GAN - Part Three - Model Training.mp4 132MB
  9. 9. Recurrent Neural Networks - RNNs/11. RNN on a Time Series - Part Two.mp4 131MB
  10. 13. Deployment/8. Live Deployment to the Web.mp4 127MB
  11. 7. Basic Artificial Neural Networks - ANNs/23. Keras Project Solutions - Categorical Data.mp4 125MB
  12. 11. AutoEncoders/3. Autoencoder for Dimensionality Reduction.mp4 117MB
  13. 7. Basic Artificial Neural Networks - ANNs/17. Keras Classification - Dealing with Overfitting and Evaluation.mp4 111MB
  14. 1. Course Overview, Installs, and Setup/3.1 FINAL_TF2_FILES.zip 99MB
  15. 1. Course Overview, Installs, and Setup/4.1 FINAL_TF2_FILES.zip 99MB
  16. 8. Convolutional Neural Networks - CNNs/7. CNN on MNIST - Part Two - Creating and Training the Model.mp4 99MB
  17. 7. Basic Artificial Neural Networks - ANNs/21. Keras Project Solutions - Dealing with Missing Data.mp4 97MB
  18. 11. AutoEncoders/4. Autoencoder for Images - Part One.mp4 94MB
  19. 4. Pandas Crash Course/8. Data Input and Output.mp4 93MB
  20. 5. Visualization Crash Course/3. Seaborn Basics.mp4 92MB
  21. 8. Convolutional Neural Networks - CNNs/14. CNN on Real Image Files - Part Three - Creating the Model.mp4 91MB
  22. 3. NumPy Crash Course/2. NumPy Arrays.mp4 89MB
  23. 8. Convolutional Neural Networks - CNNs/13. CNN on Real Image Files - Part Two - Data Processing.mp4 88MB
  24. 13. Deployment/2. Creating the Model.mp4 87MB
  25. 7. Basic Artificial Neural Networks - ANNs/22. Keras Project Solutions - Dealing with Missing Data - Part Two.mp4 85MB
  26. 7. Basic Artificial Neural Networks - ANNs/10. Keras Syntax Basics - Part Two - Creating and Training the Model.mp4 85MB
  27. 9. Recurrent Neural Networks - RNNs/8. RNN on a Sine Wave - Creating the Model.mp4 84MB
  28. 9. Recurrent Neural Networks - RNNs/9. RNN on a Sine Wave - LSTMs and Forecasting.mp4 83MB
  29. 6. Machine Learning Concepts Overview/4. Evaluating Performance - Classification Error Metrics.mp4 83MB
  30. 10. Natural Language Processing/4. NLP - Part Three - Creating Batches.mp4 82MB
  31. 8. Convolutional Neural Networks - CNNs/12. CNN on Real Image Files - Part One - Reading in the Data.mp4 81MB
  32. 7. Basic Artificial Neural Networks - ANNs/19. TensorFlow 2.0 Keras Project Notebook Overview.mp4 81MB
  33. 11. AutoEncoders/7. Autoencoder Exercise - Solutions.mp4 78MB
  34. 7. Basic Artificial Neural Networks - ANNs/13. Keras Regression Code Along - Exploratory Data Analysis - Continued.mp4 76MB
  35. 7. Basic Artificial Neural Networks - ANNs/6. Cost Functions and Gradient Descent.mp4 76MB
  36. 8. Convolutional Neural Networks - CNNs/2. Image Filters and Kernels.mp4 72MB
  37. 12. Generative Adversarial Networks/3. Creating a GAN - Part Two - The Model.mp4 70MB
  38. 13. Deployment/5. Flask Postman API.mp4 69MB
  39. 7. Basic Artificial Neural Networks - ANNs/15. Keras Regression Code Along - Model Evaluation and Predictions.mp4 69MB
  40. 10. Natural Language Processing/6. NLP - Part Five - Training the Model.mp4 65MB
  41. 7. Basic Artificial Neural Networks - ANNs/11. Keras Syntax Basics - Part Three - Model Evaluation.mp4 65MB
  42. 10. Natural Language Processing/5. NLP - Part Four - Creating the Model.mp4 64MB
  43. 8. Convolutional Neural Networks - CNNs/9. CNN on CIFAR-10 - Part One - The Data.mp4 64MB
  44. 7. Basic Artificial Neural Networks - ANNs/26. Keras Project Solutions - Model Evaluation.mp4 63MB
  45. 7. Basic Artificial Neural Networks - ANNs/4. Activation Functions.mp4 63MB
  46. 13. Deployment/4. Running a Basic Flask Application.mp4 62MB
  47. 4. Pandas Crash Course/7. Pandas Operations.mp4 61MB
  48. 11. AutoEncoders/5. Autoencoder for Images - Part Two - Noise Removal.mp4 61MB
  49. 8. Convolutional Neural Networks - CNNs/6. CNN on MNIST - Part One - The Data.mp4 60MB
  50. 8. Convolutional Neural Networks - CNNs/3. Convolutional Layers.mp4 58MB
  51. 7. Basic Artificial Neural Networks - ANNs/7. Backpropagation.mp4 58MB
  52. 12. Generative Adversarial Networks/5. DCGAN - Deep Convolutional Generative Adversarial Networks.mp4 57MB
  53. 4. Pandas Crash Course/6. GroupBy Operations.mp4 56MB
  54. 7. Basic Artificial Neural Networks - ANNs/16. Keras Classification Code Along - EDA and Preprocessing.mp4 56MB
  55. 8. Convolutional Neural Networks - CNNs/17. CNN Exercise Solutions.mp4 56MB
  56. 12. Generative Adversarial Networks/1. GANs Overview.mp4 54MB
  57. 13. Deployment/3. Model Prediction Function.mp4 53MB
  58. 10. Natural Language Processing/7. NLP - Part Six - Generating Text.mp4 52MB
  59. 4. Pandas Crash Course/10. Pandas Exercises - Solutions.mp4 51MB
  60. 7. Basic Artificial Neural Networks - ANNs/9. Keras Syntax Basics - Part One - Preparing the Data.mp4 51MB
  61. 5. Visualization Crash Course/5. Data Visualization Exercises - Solutions.mp4 50MB
  62. 9. Recurrent Neural Networks - RNNs/7. RNN on a Sine Wave - Batch Generator.mp4 50MB
  63. 3. NumPy Crash Course/4. NumPy Operations.mp4 49MB
  64. 3. NumPy Crash Course/6. Numpy Exercises - Solutions.mp4 49MB
  65. 7. Basic Artificial Neural Networks - ANNs/2. Perceptron Model.mp4 48MB
  66. 8. Convolutional Neural Networks - CNNs/15. CNN on Real Image Files - Part Four - Evaluating the Model.mp4 47MB
  67. 7. Basic Artificial Neural Networks - ANNs/14. Keras Regression Code Along - Data Preprocessing and Creating a Model.mp4 47MB
  68. 3. NumPy Crash Course/3. Numpy Index Selection.mp4 46MB
  69. 7. Basic Artificial Neural Networks - ANNs/5. Multi-Class Classification Considerations.mp4 46MB
  70. 8. Convolutional Neural Networks - CNNs/10. CNN on CIFAR-10 - Part Two - Evaluating the Model.mp4 45MB
  71. 4. Pandas Crash Course/3. Pandas DataFrames - Part One.mp4 45MB
  72. 9. Recurrent Neural Networks - RNNs/10. RNN on a Time Series - Part One.mp4 45MB
  73. 4. Pandas Crash Course/5. Pandas Missing Data.mp4 44MB
  74. 11. AutoEncoders/2. Autoencoder Basics.mp4 43MB
  75. 9. Recurrent Neural Networks - RNNs/4. LSTMS and GRU.mp4 42MB
  76. 5. Visualization Crash Course/2. Matplotlib Basics.mp4 41MB
  77. 9. Recurrent Neural Networks - RNNs/6. RNN on a Sine Wave - The Data.mp4 40MB
  78. 6. Machine Learning Concepts Overview/2. Supervised Learning Overview.mp4 40MB
  79. 8. Convolutional Neural Networks - CNNs/8. CNN on MNIST - Part Three - Model Evaluation.mp4 38MB
  80. 4. Pandas Crash Course/2. Pandas Series.mp4 38MB
  81. 4. Pandas Crash Course/4. Pandas DataFrames - Part Two.mp4 37MB
  82. 7. Basic Artificial Neural Networks - ANNs/3. Neural Networks.mp4 36MB
  83. 10. Natural Language Processing/1. Introduction to NLP Section.mp4 35MB
  84. 11. AutoEncoders/6. Autoencoder Exercise Overview.mp4 34MB
  85. 9. Recurrent Neural Networks - RNNs/5. RNN Batches.mp4 33MB
  86. 9. Recurrent Neural Networks - RNNs/2. RNN Basic Theory.mp4 30MB
  87. 9. Recurrent Neural Networks - RNNs/12. RNN Exercise.mp4 30MB
  88. 7. Basic Artificial Neural Networks - ANNs/25. Keras Project Solutions - Creating and Training a Model.mp4 30MB
  89. 8. Convolutional Neural Networks - CNNs/11. Downloading Data Set for Real Image Lectures.mp4 28MB
  90. 6. Machine Learning Concepts Overview/1. What is Machine Learning.mp4 28MB
  91. 9. Recurrent Neural Networks - RNNs/3. Vanishing Gradients.mp4 28MB
  92. 8. Convolutional Neural Networks - CNNs/4. Pooling Layers.mp4 28MB
  93. 6. Machine Learning Concepts Overview/3. Overfitting.mp4 26MB
  94. 1. Course Overview, Installs, and Setup/2. Course Overview.mp4 26MB
  95. 4. Pandas Crash Course/1. Introduction to Pandas.mp4 25MB
  96. 7. Basic Artificial Neural Networks - ANNs/24. Keras Project Solutions - Data PreProcessing.mp4 24MB
  97. 6. Machine Learning Concepts Overview/5. Evaluating Performance - Regression Error Metrics.mp4 24MB
  98. 4. Pandas Crash Course/9. Pandas Exercises.mp4 23MB
  99. 13. Deployment/1. Introduction to Deployment.mp4 23MB
  100. 10. Natural Language Processing/3. NLP - Part Two - Text Processing.mp4 23MB
  101. 5. Visualization Crash Course/4. Data Visualization Exercises.mp4 23MB
  102. 10. Natural Language Processing/2. NLP - Part One - The Data.mp4 22MB
  103. 8. Convolutional Neural Networks - CNNs/5. MNIST Data Set Overview.mp4 21MB
  104. 11. AutoEncoders/1. Introduction to Autoencoders.mp4 21MB
  105. 13. Deployment/6. Flask API - Using Requests Programmatically.mp4 20MB
  106. 12. Generative Adversarial Networks/2. Creating a GAN - Part One- The Data.mp4 19MB
  107. 6. Machine Learning Concepts Overview/6. Unsupervised Learning.mp4 19MB
  108. 8. Convolutional Neural Networks - CNNs/16. CNN Exercise Overview.mp4 18MB
  109. 3. NumPy Crash Course/5. NumPy Exercises.mp4 12MB
  110. 3. NumPy Crash Course/1. Introduction to NumPy.mp4 11MB
  111. 9. Recurrent Neural Networks - RNNs/1. RNN Section Overview.mp4 11MB
  112. 7. Basic Artificial Neural Networks - ANNs/8. TensorFlow vs. Keras Explained.mp4 10MB
  113. 7. Basic Artificial Neural Networks - ANNs/1. Introduction to ANN Section.mp4 10MB
  114. 7. Basic Artificial Neural Networks - ANNs/18. TensorFlow 2.0 Keras Project Options Overview.mp4 8MB
  115. 8. Convolutional Neural Networks - CNNs/1. CNN Section Overview.mp4 8MB
  116. 5. Visualization Crash Course/1. Introduction to Python Visualization.mp4 7MB
  117. 1. Course Overview, Installs, and Setup/3. Course Setup and Installation.srt 35KB
  118. 12. Generative Adversarial Networks/4. Creating a GAN - Part Three - Model Training.srt 34KB
  119. 9. Recurrent Neural Networks - RNNs/13. RNN Exercise - Solutions.srt 32KB
  120. 9. Recurrent Neural Networks - RNNs/11. RNN on a Time Series - Part Two.srt 31KB
  121. 7. Basic Artificial Neural Networks - ANNs/27. Tensorboard.srt 29KB
  122. 11. AutoEncoders/3. Autoencoder for Dimensionality Reduction.srt 28KB
  123. 7. Basic Artificial Neural Networks - ANNs/20. Keras Project Solutions - Exploratory Data Analysis.srt 28KB
  124. 3. NumPy Crash Course/2. NumPy Arrays.srt 27KB
  125. 7. Basic Artificial Neural Networks - ANNs/6. Cost Functions and Gradient Descent.srt 27KB
  126. 13. Deployment/7. Flask Front End.srt 26KB
  127. 9. Recurrent Neural Networks - RNNs/14. Bonus - Multivariate Time Series - RNN and LSTMs.srt 26KB
  128. 7. Basic Artificial Neural Networks - ANNs/12. Keras Regression Code Along - Exploratory Data Analysis.srt 26KB
  129. 7. Basic Artificial Neural Networks - ANNs/23. Keras Project Solutions - Categorical Data.srt 25KB
  130. 6. Machine Learning Concepts Overview/4. Evaluating Performance - Classification Error Metrics.srt 25KB
  131. 5. Visualization Crash Course/3. Seaborn Basics.srt 24KB
  132. 13. Deployment/8. Live Deployment to the Web.srt 24KB
  133. 7. Basic Artificial Neural Networks - ANNs/17. Keras Classification - Dealing with Overfitting and Evaluation.srt 24KB
  134. 11. AutoEncoders/4. Autoencoder for Images - Part One.srt 23KB
  135. 8. Convolutional Neural Networks - CNNs/7. CNN on MNIST - Part Two - Creating and Training the Model.srt 23KB
  136. 8. Convolutional Neural Networks - CNNs/13. CNN on Real Image Files - Part Two - Data Processing.srt 23KB
  137. 13. Deployment/2. Creating the Model.srt 22KB
  138. 8. Convolutional Neural Networks - CNNs/3. Convolutional Layers.srt 21KB
  139. 9. Recurrent Neural Networks - RNNs/8. RNN on a Sine Wave - Creating the Model.srt 21KB
  140. 7. Basic Artificial Neural Networks - ANNs/21. Keras Project Solutions - Dealing with Missing Data.srt 20KB
  141. 7. Basic Artificial Neural Networks - ANNs/7. Backpropagation.srt 20KB
  142. 7. Basic Artificial Neural Networks - ANNs/10. Keras Syntax Basics - Part Two - Creating and Training the Model.srt 20KB
  143. 8. Convolutional Neural Networks - CNNs/12. CNN on Real Image Files - Part One - Reading in the Data.srt 20KB
  144. 8. Convolutional Neural Networks - CNNs/14. CNN on Real Image Files - Part Three - Creating the Model.srt 20KB
  145. 4. Pandas Crash Course/7. Pandas Operations.srt 19KB
  146. 7. Basic Artificial Neural Networks - ANNs/13. Keras Regression Code Along - Exploratory Data Analysis - Continued.srt 18KB
  147. 9. Recurrent Neural Networks - RNNs/9. RNN on a Sine Wave - LSTMs and Forecasting.srt 18KB
  148. 8. Convolutional Neural Networks - CNNs/2. Image Filters and Kernels.srt 18KB
  149. 10. Natural Language Processing/4. NLP - Part Three - Creating Batches.srt 18KB
  150. 8. Convolutional Neural Networks - CNNs/6. CNN on MNIST - Part One - The Data.srt 18KB
  151. 4. Pandas Crash Course/3. Pandas DataFrames - Part One.srt 17KB
  152. 12. Generative Adversarial Networks/3. Creating a GAN - Part Two - The Model.srt 17KB
  153. 7. Basic Artificial Neural Networks - ANNs/22. Keras Project Solutions - Dealing with Missing Data - Part Two.srt 17KB
  154. 4. Pandas Crash Course/8. Data Input and Output.srt 17KB
  155. 7. Basic Artificial Neural Networks - ANNs/11. Keras Syntax Basics - Part Three - Model Evaluation.srt 17KB
  156. 9. Recurrent Neural Networks - RNNs/4. LSTMS and GRU.srt 17KB
  157. 8. Convolutional Neural Networks - CNNs/9. CNN on CIFAR-10 - Part One - The Data.srt 16KB
  158. 7. Basic Artificial Neural Networks - ANNs/4. Activation Functions.srt 16KB
  159. 7. Basic Artificial Neural Networks - ANNs/5. Multi-Class Classification Considerations.srt 16KB
  160. 7. Basic Artificial Neural Networks - ANNs/15. Keras Regression Code Along - Model Evaluation and Predictions.srt 16KB
  161. 13. Deployment/4. Running a Basic Flask Application.srt 15KB
  162. 3. NumPy Crash Course/3. Numpy Index Selection.srt 15KB
  163. 4. Pandas Crash Course/5. Pandas Missing Data.srt 15KB
  164. 13. Deployment/5. Flask Postman API.srt 15KB
  165. 7. Basic Artificial Neural Networks - ANNs/9. Keras Syntax Basics - Part One - Preparing the Data.srt 15KB
  166. 7. Basic Artificial Neural Networks - ANNs/2. Perceptron Model.srt 15KB
  167. 10. Natural Language Processing/5. NLP - Part Four - Creating the Model.srt 14KB
  168. 4. Pandas Crash Course/6. GroupBy Operations.srt 14KB
  169. 11. AutoEncoders/7. Autoencoder Exercise - Solutions.srt 14KB
  170. 10. Natural Language Processing/6. NLP - Part Five - Training the Model.srt 14KB
  171. 4. Pandas Crash Course/4. Pandas DataFrames - Part Two.srt 14KB
  172. 9. Recurrent Neural Networks - RNNs/10. RNN on a Time Series - Part One.srt 14KB
  173. 7. Basic Artificial Neural Networks - ANNs/26. Keras Project Solutions - Model Evaluation.srt 13KB
  174. 5. Visualization Crash Course/2. Matplotlib Basics.srt 13KB
  175. 4. Pandas Crash Course/2. Pandas Series.srt 12KB
  176. 13. Deployment/3. Model Prediction Function.srt 12KB
  177. 7. Basic Artificial Neural Networks - ANNs/19. TensorFlow 2.0 Keras Project Notebook Overview.srt 12KB
  178. 6. Machine Learning Concepts Overview/2. Supervised Learning Overview.srt 12KB
  179. 9. Recurrent Neural Networks - RNNs/6. RNN on a Sine Wave - The Data.srt 12KB
  180. 8. Convolutional Neural Networks - CNNs/15. CNN on Real Image Files - Part Four - Evaluating the Model.srt 12KB
  181. 9. Recurrent Neural Networks - RNNs/5. RNN Batches.srt 12KB
  182. 6. Machine Learning Concepts Overview/3. Overfitting.srt 12KB
  183. 7. Basic Artificial Neural Networks - ANNs/14. Keras Regression Code Along - Data Preprocessing and Creating a Model.srt 12KB
  184. 12. Generative Adversarial Networks/1. GANs Overview.srt 12KB
  185. 3. NumPy Crash Course/4. NumPy Operations.srt 12KB
  186. 10. Natural Language Processing/7. NLP - Part Six - Generating Text.srt 12KB
  187. 8. Convolutional Neural Networks - CNNs/17. CNN Exercise Solutions.srt 12KB
  188. 9. Recurrent Neural Networks - RNNs/2. RNN Basic Theory.srt 11KB
  189. 11. AutoEncoders/2. Autoencoder Basics.srt 11KB
  190. 11. AutoEncoders/5. Autoencoder for Images - Part Two - Noise Removal.srt 11KB
  191. 9. Recurrent Neural Networks - RNNs/7. RNN on a Sine Wave - Batch Generator.srt 11KB
  192. 7. Basic Artificial Neural Networks - ANNs/16. Keras Classification Code Along - EDA and Preprocessing.srt 11KB
  193. 9. Recurrent Neural Networks - RNNs/3. Vanishing Gradients.srt 11KB
  194. 5. Visualization Crash Course/5. Data Visualization Exercises - Solutions.srt 11KB
  195. 7. Basic Artificial Neural Networks - ANNs/3. Neural Networks.srt 11KB
  196. 3. NumPy Crash Course/6. Numpy Exercises - Solutions.srt 11KB
  197. 8. Convolutional Neural Networks - CNNs/10. CNN on CIFAR-10 - Part Two - Evaluating the Model.srt 10KB
  198. 4. Pandas Crash Course/10. Pandas Exercises - Solutions.srt 10KB
  199. 8. Convolutional Neural Networks - CNNs/4. Pooling Layers.srt 10KB
  200. 12. Generative Adversarial Networks/5. DCGAN - Deep Convolutional Generative Adversarial Networks.srt 10KB
  201. 8. Convolutional Neural Networks - CNNs/8. CNN on MNIST - Part Three - Model Evaluation.srt 10KB
  202. 10. Natural Language Processing/1. Introduction to NLP Section.srt 9KB
  203. 8. Convolutional Neural Networks - CNNs/11. Downloading Data Set for Real Image Lectures.srt 9KB
  204. 6. Machine Learning Concepts Overview/5. Evaluating Performance - Regression Error Metrics.srt 8KB
  205. 6. Machine Learning Concepts Overview/1. What is Machine Learning.srt 8KB
  206. 1. Course Overview, Installs, and Setup/2. Course Overview.srt 7KB
  207. 6. Machine Learning Concepts Overview/6. Unsupervised Learning.srt 7KB
  208. 8. Convolutional Neural Networks - CNNs/5. MNIST Data Set Overview.srt 7KB
  209. 10. Natural Language Processing/2. NLP - Part One - The Data.srt 7KB
  210. 9. Recurrent Neural Networks - RNNs/12. RNN Exercise.srt 7KB
  211. 12. Generative Adversarial Networks/2. Creating a GAN - Part One- The Data.srt 6KB
  212. 4. Pandas Crash Course/1. Introduction to Pandas.srt 6KB
  213. 10. Natural Language Processing/3. NLP - Part Two - Text Processing.srt 6KB
  214. 7. Basic Artificial Neural Networks - ANNs/25. Keras Project Solutions - Creating and Training a Model.srt 6KB
  215. 13. Deployment/6. Flask API - Using Requests Programmatically.srt 6KB
  216. 13. Deployment/1. Introduction to Deployment.srt 5KB
  217. 1. Course Overview, Installs, and Setup/4. FAQ - Frequently Asked Questions.html 5KB
  218. 11. AutoEncoders/6. Autoencoder Exercise Overview.srt 5KB
  219. 5. Visualization Crash Course/4. Data Visualization Exercises.srt 5KB
  220. 11. AutoEncoders/1. Introduction to Autoencoders.srt 5KB
  221. 7. Basic Artificial Neural Networks - ANNs/24. Keras Project Solutions - Data PreProcessing.srt 5KB
  222. 4. Pandas Crash Course/9. Pandas Exercises.srt 4KB
  223. 9. Recurrent Neural Networks - RNNs/1. RNN Section Overview.srt 4KB
  224. 8. Convolutional Neural Networks - CNNs/16. CNN Exercise Overview.srt 4KB
  225. 3. NumPy Crash Course/1. Introduction to NumPy.srt 3KB
  226. 7. Basic Artificial Neural Networks - ANNs/1. Introduction to ANN Section.srt 3KB
  227. 7. Basic Artificial Neural Networks - ANNs/8. TensorFlow vs. Keras Explained.srt 3KB
  228. 7. Basic Artificial Neural Networks - ANNs/18. TensorFlow 2.0 Keras Project Options Overview.srt 3KB
  229. 8. Convolutional Neural Networks - CNNs/1. CNN Section Overview.srt 2KB
  230. 3. NumPy Crash Course/5. NumPy Exercises.srt 2KB
  231. 5. Visualization Crash Course/1. Introduction to Python Visualization.srt 2KB
  232. 1. Course Overview, Installs, and Setup/1. Auto-Welcome Message.html 1KB
  233. 10. Natural Language Processing/How you can help GetFreeCourses.Co.txt 182B
  234. 4. Pandas Crash Course/How you can help GetFreeCourses.Co.txt 182B
  235. 7. Basic Artificial Neural Networks - ANNs/How you can help GetFreeCourses.Co.txt 182B
  236. How you can help GetFreeCourses.Co.txt 182B
  237. 2. COURSE OVERVIEW CONFIRMATION/1. PLEASE WATCH COURSE OVERVIEW LECTURE.html 165B
  238. 9. Recurrent Neural Networks - RNNs/4.2 How to choose between LSTM vs GRU.html 140B
  239. 1. Course Overview, Installs, and Setup/3.2 requirements.txt 138B
  240. 8. Convolutional Neural Networks - CNNs/11.1 Direct Link to Download cell_images.zip (Note You can't preview a zip file) Just download it..html 127B
  241. 10. Natural Language Processing/Download Paid Udemy Courses For Free.url 116B
  242. 10. Natural Language Processing/GetFreeCourses.Co.url 116B
  243. 4. Pandas Crash Course/Download Paid Udemy Courses For Free.url 116B
  244. 4. Pandas Crash Course/GetFreeCourses.Co.url 116B
  245. 7. Basic Artificial Neural Networks - ANNs/Download Paid Udemy Courses For Free.url 116B
  246. 7. Basic Artificial Neural Networks - ANNs/GetFreeCourses.Co.url 116B
  247. 9. Recurrent Neural Networks - RNNs/4.3 Famous Karpathy Blog Post.html 116B
  248. Download Paid Udemy Courses For Free.url 116B
  249. GetFreeCourses.Co.url 116B
  250. 9. Recurrent Neural Networks - RNNs/4.1 Wikipedia Article Describing LSTM Variants.html 113B
  251. 7. Basic Artificial Neural Networks - ANNs/7.1 Great walkthrough for BackPropagation!.html 112B
  252. 9. Recurrent Neural Networks - RNNs/4.4 Great Blog Post on Exploring LSTM Neurons.html 109B