a book about love

The significantly expanded and updated new edition of a widely used text on reinforcement learning, one of the most active research areas in artificial intelligence. Reinforcement learning, one of the most active research areas in artificial intelligence, is a computational approach to learning whereby an agent tries to maximize the total amount of reward it receives while inte...(展开全部)

いつだって、この出会いは必然だった―― 第24回電撃小説大賞《金賞》受賞作! ――これは僕が失った、二百十四回にも及ぶ一週間の恋の話。 そして、わたしが手にした、四年に及ぶ一度きりの恋の話。 「ねえ、由くん。わたしはあなたが――」 初めて聞いたその声に足を止める。学校からの帰り道。中学のグラウンドや、駅前の本屋。それから白い猫が眠る空き地の中で、なぜだか僕のことを知っている不思議な少女・椎名由希は、いつもそんな風に声をかけてきた。 笑って、泣いて、怒って、手を繋いで。 僕たちは何度も、消えていく思い出を、どこにも存在しない約束を重ねていく。 だから、僕は何も知らなかったんだ。 由希が浮かべた笑顔の価値も、零した涙の意味も。たくさんの「初めまして」に込められた、たった一つの想いすら。 ――これは残酷なまでに切なく、心を捉えて離さない、出会いと別れの物語...(展开全部)

★重複不斷的時光，編織著難以言喻的愛戀。 ★悲傷到接近殘酷，讓人揪心不已，關於相遇與離別的故事。 ★第24屆電擊小說大賞《金賞》作品登場！ ★首刷限定，隨書附贈4P特典小冊子！ 「吶，小由。我──」 一道初次耳聞的聲音，讓我停下腳步。 在從學校回家的路上、國中操場上、 車站前的書店，或是某隻白貓沉睡的空地上， 不知為何認識我的神祕少女──椎名由希，總會像這樣向我搭話。 歡笑、哭泣、生氣、牽手。 我們不斷累積終將消失的回憶，立下許多不存在的約定。 所以，我一無所知。 無論是浮現在由希臉上的笑容的價值、流下的眼淚的意義， 還是包含在無數次「初次見面」當中的唯一一份心意。 這是一個悲傷到接近殘酷，讓人揪心不已，關於相遇（春）與離別（雪）的故事。 ©AYA HAZUKI 2018

Reinforcement Learning (RL) is the trending and most promising branch of artificial intelligence. This Learning Path will help you master not only the basic reinforcement learning algorithms but also the advanced deep reinforcement learning algorithms.The Learning Path starts with an introduction to RL followed by OpenAI Gym, and TensorFlow. You will then explore various RL algorithms, such as Markov Decision Process, Monte Carlo methods, and dynamic programming, including value and policy iteration. You'll also work on various datasets including image, text, and video. This example-rich guide will introduce you to deep RL algorithms, such as Dueling DQN, DRQN, A3C, PPO, and TRPO. You will gain experience in several domains, including gaming, image processing, and physical simulations. You'll explore TensorFlow and OpenAI Gym to implement algorithms that also predict stock prices, generate natural language, and even build other neural networks. You will also learn about imagination-augmented agents, learning from human preference, DQfD, HER, and many of the recent advancements in RL.By the end of the Learning Path, you will have all the knowledge and experience needed to implement RL and deep RL in your projects, and you enter the world of artificial intelligence to solve various real-life problems.This Learning Path includes content from the following Packt products:Hands-On Reinforcement Learning with Python by Sudharsan Ravichandiran.Python Reinforcement Learning Projects by Sean Saito, Yang Wenzhuo, and Rajalingappaa Shanmugamani.

Reinforcement Learning (RL) is the trending and most promising branch of artificial intelligence. This Learning Path will help you master not only the basic reinforcement learning algorithms but also the advanced deep reinforcement learning algorithms.The Learning Path starts with an introduction to RL followed by OpenAI Gym, and TensorFlow. You will then explore various RL algorithms, such as Markov Decision Process, Monte Carlo methods, and dynamic programming, including value and policy iteration. You'll also work on various datasets including image, text, and video. This example-rich guide will introduce you to deep RL algorithms, such as Dueling DQN, DRQN, A3C, PPO, and TRPO. You will gain experience in several domains, including gaming, image processing, and physical simulations. You'll explore TensorFlow and OpenAI Gym to implement algorithms that also predict stock prices, generate natural language, and even build other neural networks. You will also learn about imagination-augmented agents, learning from human preference, DQfD, HER, and many of the recent advancements in RL.By the end of the Learning Path, you will have all the knowledge and experience needed to implement RL and deep RL in your projects, and you enter the world of artificial intelligence to solve various real-life problems.This Learning Path includes content from the following Packt products:Hands-On Reinforcement Learning with Python by Sudharsan Ravichandiran.Python Reinforcement Learning Projects by Sean Saito, Yang Wenzhuo, and Rajalingappaa Shanmugamani.

Eve Bunting addresses the social issue of the elderly or unwell grandparents and how even a child can offer real consolation to them.

Reinforcement learning, one of the most active research areas in artificial intelligence, is a computational approach to learning whereby an agent tries to maximize the total amount of reward it receives when interacting with a complex, uncertain environment. In Reinforcement Learning, Richard Sutton and Andrew Barto provide a clear and simple account of the key ideas and algor...(展开全部)

#文中任何地名、校名等，请不要上升到现实高度!只是为了更有现实感而不作修改!我对它们没有任何意见!还有出现的任何医学相关情节不保真，不要细究。以“人”为核心的故事。27岁的正在后期研修的心内科医生白石藏之介被一纸诉状送上了法庭，与森川葵的人生就此交汇。无论做什么都要完美，抱着这样的觉悟，带着包括忍足谦也在内的同伴的守望，他踏上了抓取远大前程的未来。white stone be ambitious!医科大学毕业后和白石进入同一家医院研修的儿科医生忍足谦也，今天也在苦恼没有进展的实验与论文，讨厌等待却不得不等待一个结果。感情线只是一部分。创作的目的，应该就是想看喜来喜这种看似完美，理所应当的平稳感情下却暗藏自己造成的危机。还有想看他和谦也的扶持，好兄弟一生一世一起走。除此之外，就是寄托理想色彩给原创角色森川小姐——真正的英雄主义。以及所有与中心主角喜来喜相关的人构成的核心主题——no man is an island。「あかん、これ……まさかの頻脈ちゃうん!?」「は、はあ!?ちょ、頻脈って……えっ、大丈夫！?救急車、救急車呼ぶ！？ 呼ぶで!?」虽然人生是搞笑者为王，但请不要在这个告白重要时刻装傻和吐槽!「んん~~Ecstasy!」这是白石「愛と勇気の花束、ぜんぶまとめてプレゼント！」这是森川「No Speed No Life!俺は浪速のスピードスター！」这是谦也

简介：日常。