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Results 31-36 of 36 (Search time: 0.065 seconds).
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  • Sách/Book

  • Hesitant Fuzzy Set: Theory and Extension

    • Authors: Bahram Farhadinia (2021)

  • Presenting the review of many and important types of hesitant fuzzy extensions, and including references to a large number of related publications, this book will serve as a useful reference book for researchers in this field.
  • Sách/Book

  • Fundamentals of Logic and Computation: With Practical Automated Reasoning and Verification

    • Authors: Hou, Zhe (2021)

  • This textbook aims to help the reader develop an in-depth understanding of logical reasoning and gain knowledge of the theory of computation. The book combines theoretical teaching and practical exercises; the latter is realised in Isabelle/HOL, a modern theorem prover, and PAT, an industry-scale model checker. I also give entry-level tutorials on the two software to help the reader get started.
  • Sách/Book

  • Machine Learning with Quantum Computers

    • Authors: Maria Schuld (2021)

  • This book offers an introduction into quantum machine learning research, covering approaches that range from "near-term" to fault-tolerant quantum machine learning algorithms, and from theoretical to practical techniques that help us understand how quantum computers can learn from data.
  • Sách/Book

  • Grokking Deep Reinforcement Learning

    • Authors: Miguel Morales (2021)

  • This common pattern is the foundation of deep reinforcement learning: building machine learning systems that explore and learn based on the responses of the environment.