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种子名称：
[FreeCoursesOnline.Me] [Packt] Mastering Deep Learning using Apache Spark [FCO]
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视频
文件数目：
29个文件
文件大小：
638.82 MB
收录时间：
2021-5-3 14:58
已经下载：
3次
资源热度：
135
最近下载：
2024-5-25 00:34
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[FreeCoursesOnline.Me] [Packt] Mastering Deep Learning using Apache Spark [FCO].torrent
1. CONVOLUTIONAL NEURAL NETWORKS FOR SPEECH RECOGNITION (NLP)/1. The Course Overview-111792.mp416.97MB
1. CONVOLUTIONAL NEURAL NETWORKS FOR SPEECH RECOGNITION (NLP)/2. Analyzing Input Text Data That Will Need to Be Classified-111793.mp453.89MB
1. CONVOLUTIONAL NEURAL NETWORKS FOR SPEECH RECOGNITION (NLP)/3. Configuring Word Vectors That Will Be Used in Our Network-111794.mp414.29MB
1. CONVOLUTIONAL NEURAL NETWORKS FOR SPEECH RECOGNITION (NLP)/4. Adding Layers to Deep Neural Network-111795.mp414.65MB
1. CONVOLUTIONAL NEURAL NETWORKS FOR SPEECH RECOGNITION (NLP)/5. Asserting Classification of Input Sentences-111796.mp416.06MB
2. PERFORMING VIDEO CLASSIFICATION USING RNN AND LSTMS/6. Generating Input Video Data-111798.mp422.08MB
2. PERFORMING VIDEO CLASSIFICATION USING RNN AND LSTMS/7. Creating a Neural Network for Video Classification-111799.mp418.28MB
2. PERFORMING VIDEO CLASSIFICATION USING RNN AND LSTMS/8. Adding RNN and LSTMs to Network to Perform a Task Better-111800.mp419.03MB
2. PERFORMING VIDEO CLASSIFICATION USING RNN AND LSTMS/9. Testing and Validating Deep Learning Model-111801.mp424.45MB
3. TRANSFER LEARNING AND PRE-TRAINED MODELS/10. Creating Paragraph Vectors-111803.mp49.4MB
3. TRANSFER LEARNING AND PRE-TRAINED MODELS/11. Adding Labels to Non-Labelled Data-111804.mp417.56MB
3. TRANSFER LEARNING AND PRE-TRAINED MODELS/12. Finding Similarity between Vectors-111805.mp416.58MB
3. TRANSFER LEARNING AND PRE-TRAINED MODELS/13. Creating a Model That Can Guess the Meaning of The Word-111806.mp414.43MB
4. DEEP REINFORCEMENT LEARNING/14. Anomaly Detection Problem Explained-111808.mp427.33MB
4. DEEP REINFORCEMENT LEARNING/15. Extracting Features from Input Data Using Multi-Layer Approach-111809.mp426.68MB
4. DEEP REINFORCEMENT LEARNING/16. Adding Layer That Finds an Actual Anomaly-111810.mp417MB
4. DEEP REINFORCEMENT LEARNING/17. Testing and Validating Results from Our Deep Learning Model-111811.mp417.37MB
5. GENERATIVE ADVERSARIAL NETWORKS/18. Creating Data Generator for GAN-111813.mp419.36MB
5. GENERATIVE ADVERSARIAL NETWORKS/19. Adding Discriminator for Our Data-111814.mp430.95MB
5. GENERATIVE ADVERSARIAL NETWORKS/20. Create Classifier for Generated Data-111815.mp424.25MB
5. GENERATIVE ADVERSARIAL NETWORKS/21. Performing Validation of Our Model-111816.mp416.51MB
6. DISTRIBUTED MODELS/22. Configuring Spark for High Data Distribution-111818.mp416.03MB
6. DISTRIBUTED MODELS/23. Fetching Input Set into Distributed Data Set Using Spark API-111819.mp414.16MB
6. DISTRIBUTED MODELS/24. Creating Training Master That Supervise Computations on the Workers-111820.mp413.62MB
6. DISTRIBUTED MODELS/25. Evaluating Speed of Distributed Training Using Spark-111821.mp49.9MB
7. TROUBLESHOOTING/26. Monitoring of Models Using Spark UI-111823.mp411.79MB
7. TROUBLESHOOTING/27. Speeding Up Computations by Employing Caching-111824.mp414.54MB
7. TROUBLESHOOTING/28. Partitioning Deep Learning Data into Several Workers-111825.mp464.75MB
7. TROUBLESHOOTING/29. Tweaking Spark Workers Configuration-111826.mp456.91MB
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