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Applied machine learning with a solid foundation in theory. Revised and expanded for TensorFlow 2, GANs, and reinforcement learning.Purchase of the print or Kindle book includes a …
Get more from your data by creating practical machine learning systems with PythonKey FeaturesDevelop your own Python-based machine learning systemDiscover how Python offers …
Unlock modern machine learning and deep learning techniques with Python by using the latest cutting-edge open source Python libraries. About This Book • Second edition of the …
Implement supervised and unsupervised machine learning algorithms using C++ libraries such as PyTorch C++ API, Caffe2, Shogun, Shark-ML, mlpack, and dlib with the help of …
Comprehensive recipes to give you valuable insights on Transformers, Reinforcement Learning, and moreKey FeaturesDeep Learning solutions from Kaggle Masters and Google Developer …
Manage different business scenarios with the right machine learning technique using Google's highly scalable BigQuery MLKey FeaturesGain a clear understanding of AI and machine …
Fintech veteran and venture capitalist, Arunkumar Krishnakumar, cuts through the hype to bring us a first-hand look into how quantum computing and Blockchain together could …
Written as a tutorial to explore and understand the power of R for machine learning. This practical guide that covers all of the need to know topics in a very systematic way. For …
Learning how to apply unsupervised algorithms on unlabeled datasets from scratch can be easier than you thought with this beginner's workshop, featuring interesting examples and …
Master machine learning techniques with R to deliver insights in complex projects About This Book • Understand and apply machine learning methods using an extensive set of R …