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Hands-On Artificial Intelligence with TensorFlow: Useful techniques in machine learning and deep learning for building intelligent applications - Softcover
Synopsis
Useful techniques in machine learning and deep learning for building intelligent applications
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About the Author
Amir Ziai is proficient inBuilding machine learning platforms and applications. Passionate about implementing efficient and scalable algorithms for optimizing supervised machine learning workflows, ranging from feature engineering to model tuning and model serving. Teaching, mentoring, and blogging about machine learning and data science. Keeping my skills sharp by closely following and integrating leading research papers and open-source projects out of academia and the industry. Using Scala, Spark, H2O, Vowpal Wabbit, EMR, Python, scikit-learn, XGBoost, C++, keras, and TensorFlow.
Quan Hua is a Computer Vision and Machine Learning Engineer at BodiData, a data platform for body measurements, where he focuses on developing computer vision and machine learning applications for a handheld technology capable of acquiring a body avatar while a person is fully clothed. He earned a bachelor of science degree from the University of Science, Vietnam, specializing in Computer Vision. He has been working in the field of computer vision and machine learning for about 3 years at start-ups. Quan has been writing for Packt since 2015 for a Computer Vision book, OpenCV 3 Blueprints.
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