What's New in TensorFlow 2.0
Use the new and improved features of TensorFlow to enhance machine learning and deep learning
Ajay Baranwal, Alizishaan Khatri & Tanish Baranwal
What's New in TensorFlow 2.0
Use the new and improved features of TensorFlow to enhance machine learning and deep learning
Ajay Baranwal, Alizishaan Khatri & Tanish Baranwal
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Omschrijving
This book will cover all the new features that have been introduced in TensorFlow 2.0 especially the major highlight, including eager execution and more. You will learn how to make the best use of these features to migrate your codes from TensorFlow 1.x to TensorFlow 2.0 in a seamless way.
Ajay Baranwal works as a director at the Center for Deep Learning in Electronics Manufacturing, where he is responsible for researching and developing TensorFlow-based deep learning applications in the semiconductor and electronics manufacturing industry. Part of his role is to teach and train deep learning techniques to professionals. He has a solid history of software engineering and management, where he got hooked on deep learning. He moved to natural language understanding (NLU) to pursue deep learning further at Abzooba and built an information retrieval system for the finance sector. He has also worked at Ansys Inc. as a senior manager (engineering) and a technical fellow (data science) and introduced several ML applications. Alizishaan Khatri works as a machine learning engineer in Silicon Valley. He uses TensorFlow to build, design, and maintain production-grade systems that use deep learning for NLP applications. A major system he has built is a deep learning-based system for detecting offensive content in chats. Other works he has done includes text classification and named entity recognition (NER) systems for different use cases. He is passionate about sharing ideas with the community and frequently speaks at tech conferences across the globe. He holds a master's degree in computer science from the SUNY Buffalo University. His thesis proposed a solution to the problem of overfitting in deep learning. Outside of his work, he enjoys skiing and mountaineering. Tanish Baranwal is a sophomore in high school and lives in California with his family and has worked with his dad on deep learning projects using TensorFlow for the last 3 years. He has been coding for 9 years (since 1st grade) and is well versed in Python and JavaScript. He is now learning C++. He has certificates from various online courses and has won the Entrepreneurship Showcase Award at his school. Some of his deep learning projects include anomaly detection systems for transaction fraud, a system to save energy by turning off domestic water heaters when not in use, and a fully functional style transfer program that can recreate any photograph in another style. He has also written blogs on deep learning on Medium with over 1,000 views.
Ajay Baranwal works as a director at the Center for Deep Learning in Electronics Manufacturing, where he is responsible for researching and developing TensorFlow-based deep learning applications in the semiconductor and electronics manufacturing industry. Part of his role is to teach and train deep learning techniques to professionals. He has a solid history of software engineering and management, where he got hooked on deep learning. He moved to natural language understanding (NLU) to pursue deep learning further at Abzooba and built an information retrieval system for the finance sector. He has also worked at Ansys Inc. as a senior manager (engineering) and a technical fellow (data science) and introduced several ML applications. Alizishaan Khatri works as a machine learning engineer in Silicon Valley. He uses TensorFlow to build, design, and maintain production-grade systems that use deep learning for NLP applications. A major system he has built is a deep learning-based system for detecting offensive content in chats. Other works he has done includes text classification and named entity recognition (NER) systems for different use cases. He is passionate about sharing ideas with the community and frequently speaks at tech conferences across the globe. He holds a master's degree in computer science from the SUNY Buffalo University. His thesis proposed a solution to the problem of overfitting in deep learning. Outside of his work, he enjoys skiing and mountaineering. Tanish Baranwal is a sophomore in high school and lives in California with his family and has worked with his dad on deep learning projects using TensorFlow for the last 3 years. He has been coding for 9 years (since 1st grade) and is well versed in Python and JavaScript. He is now learning C++. He has certificates from various online courses and has won the Entrepreneurship Showcase Award at his school. Some of his deep learning projects include anomaly detection systems for transaction fraud, a system to save energy by turning off domestic water heaters when not in use, and a fully functional style transfer program that can recreate any photograph in another style. He has also written blogs on deep learning on Medium with over 1,000 views.