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TensorFlow Complete Training 2024
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00:00 Welcome to Course
00:48 Introduction to Machine Learning and TensorFlow
34:04 Installation and Setup
01:09:05 Tensors and Operations
01:19:32 Graphs and Sessions
01:31:47 Basic Neural Networks with TensorFlow
01:48:11 Customizing Models with Keras
02:03:35 Convolutional Neural Networks (CNNs)
02:17:34 Recurrent Neural Networks (RNNs)
02:30:00 Deploying TensorFlow Models
02:44:29 Distributed TensorFlow
03:01:34 TensorFlow Extended (TFX)
03:17:28 Real-world Applications
03:40:02 Hands-on Projects
04:01:08 Advanced Topics and Future Directions
04:17:23 Resources and Community
04:29:22 Wrapping Up
TensorFlow, a powerful open-source machine learning framework, enables building and training diverse models with its flexible architecture and high-level APIs like Keras.
Key concepts include tensors, computational graphs, neural networks, and deployment tools like TensorFlow Serving. Next steps involve exploring advanced topics, contributing to the community, engaging in real-world projects, and continuous learning.
TensorFlow Extended (TFX) facilitates end-to-end ML pipelines. By mastering TensorFlow's capabilities, users can deploy models in production environments, contribute to open-source projects, and stay updated with industry trends, empowering them to solve complex problems and advance their careers in machine learning.
00:48 Introduction to Machine Learning and TensorFlow
34:04 Installation and Setup
01:09:05 Tensors and Operations
01:19:32 Graphs and Sessions
01:31:47 Basic Neural Networks with TensorFlow
01:48:11 Customizing Models with Keras
02:03:35 Convolutional Neural Networks (CNNs)
02:17:34 Recurrent Neural Networks (RNNs)
02:30:00 Deploying TensorFlow Models
02:44:29 Distributed TensorFlow
03:01:34 TensorFlow Extended (TFX)
03:17:28 Real-world Applications
03:40:02 Hands-on Projects
04:01:08 Advanced Topics and Future Directions
04:17:23 Resources and Community
04:29:22 Wrapping Up
TensorFlow, a powerful open-source machine learning framework, enables building and training diverse models with its flexible architecture and high-level APIs like Keras.
Key concepts include tensors, computational graphs, neural networks, and deployment tools like TensorFlow Serving. Next steps involve exploring advanced topics, contributing to the community, engaging in real-world projects, and continuous learning.
TensorFlow Extended (TFX) facilitates end-to-end ML pipelines. By mastering TensorFlow's capabilities, users can deploy models in production environments, contribute to open-source projects, and stay updated with industry trends, empowering them to solve complex problems and advance their careers in machine learning.
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