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Basic to Advanced Training in TensorFlow
Updated on Sep, 2026
Programming, Data Science, Python
Duration - 4.5 hours
Training 5 or more people ?
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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.
2. Computational Graph:
4. Variables and Operations:
6. Training and Optimization:
7. Deployment and Serving:
8. TensorFlow Extended (TFX):
9. TensorFlow Quantum (TFQ):
Check out the detailed breakdown of what’s inside the course
After completing my Master's in Computer Science at George Washington University, started working on Web and Mobile Applications. Have been training people in Mobile Technologies since 2009 in both iOS and Android Technology.
Been building Mobile Apps and Websites since 2002 for brands like Delta Air Lines, The Washington Post, Cars, Kaplan, and many more. Have more than 150 mobile applications of my own.
Hands-on experience architecting, developing, and publishing apps since 2009.
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