江流深对某当红新人歌手的印象： 小王八蛋！早晚要糊！→ ……咦小朋友有点意思 → 艾艾好可爱 → 想【】 夏希艾对某超一线影帝的印象： 风流多情，优雅绅士 → ……流氓 → ……流氓 → ……老流氓！ （其实是个互相救赎互相宠爱的正经娱乐圈文。） cp：江流深X夏希艾 骚话影帝X盐系歌手， 走剧情走感情，基本无虐轻松向。

There's only one you in this great big world. Make it a better place. Adri's mama and papa share some of the wisdom they have gained through the years with their eager son. Their words, simple and powerful, are meant to comfort and guide him as he goes about exploring the world. This exquisitely illustrated book explodes with color and honest insights. Kranz's uniquely painted ...(展开全部)

There's only one you in this great big world. Make it a better place. Adri's mama and papa share some of the wisdom they have gained through the years with their eager son. Their words, simple and powerful, are meant to comfort and guide him as he goes about exploring the world. This exquisitely illustrated book explodes with color and honest insights. Kranz's uniquely painted ...(展开全部)

正巫/白菇/龙卡/高雨等

正巫/白菇/龙卡/高雨等

A young woman holds her newborn son And looks at him lovingly. Softly she sings to him: "I'll love you forever I'll like you for always As long as I'm living My baby you'll be" So begins the story that has touched the hearts of millions of Americans. Since publication in l986, "Love You Forever" has sold more than 15 million copies in paperback and the regular hardcove...(展开全部)

伊坂幸太郎 1971年出生于千叶县。毕业于日本东北大学法学系。2000年以《奥杜邦的祈祷》获第5届新潮推理俱乐部奖，成为职业作家。2003年，《重力小丑》入围直木奖，并和《阳光劫匪倒转地球》一起入选“这本推理小说了不起！”的前10名，吸引了更多关注。2004年，《家鸭与野鸭的投币式寄物柜》获第25届吉川英治文学新人奖，《死神的精确度》获第57届日本推理作家协会奖（短篇部门）。著有《死神的精确度》《魔王》《沙漠》《末日的愚者》《阳光劫匪日常与袭击》《一首朋克救地球》等。 ———————————————— 石田衣良 1960年出生于东京都。毕业于成蹊大学经济学系。入职广告制作公司之后，作为一名广告文案活跃于业界。1997年，凭借《池袋西口公园》获第36届“ALL读物推理小说新人奖”，成为职业作家。翌年，同名短篇小说集的单行本出版发行，拍成电视剧后引起讨论...(展开全部)

伊坂幸太郎 1971年出生于千叶县。毕业于日本东北大学法学系。2000年以《奥杜邦的祈祷》获第5届新潮推理俱乐部奖，成为职业作家。2003年，《重力小丑》入围直木奖，并和《阳光劫匪倒转地球》一起入选“这本推理小说了不起！”的前10名，吸引了更多关注。2004年，《家鸭与野鸭的投币式寄物柜》获第25届吉川英治文学新人奖，《死神的精确度》获第57届日本推理作家协会奖（短篇部门）。著有《死神的精确度》《魔王》《沙漠》《末日的愚者》《阳光劫匪日常与袭击》《一首朋克救地球》等。 ———————————————— 石田衣良 1960年出生于东京都。毕业于成蹊大学经济学系。入职广告制作公司之后，作为一名广告文案活跃于业界。1997年，凭借《池袋西口公园》获第36届“ALL读物推理小说新人奖”，成为职业作家。翌年，同名短篇小说集的单行本出版发行，拍成电视剧后引起讨论...(展开全部)

With information on the web exponentially increasing, it has become more difficult than ever to navigate through everything to find reliable content that will help you get started with deep learning. This book is designed to help you if you’re a beginner looking to work on deep learning and build deep learning models from scratch, and already have the basic mathematical and programming knowledge required to get started.The book begins with a basic overview of machine learning, guiding you through setting up popular Python frameworks. You will also understand how to prepare data by cleaning and preprocessing it for deep learning, and gradually go on to explore neural networks. A dedicated section will give you insights into the working of neural networks by helping you get hands-on with training single and multiple layers of neurons. Later, you will cover popular neural network architectures such as CNNs, RNNs, AEs, VAEs, and GANs with the help of simple examples, and you will even build models from scratch. At the end of each chapter, you will find a question and answer section to help you test what you’ve learned through the course of the book.By the end of this book, you’ll be well-versed with deep learning concepts and have the knowledge you need to use specific algorithms with various tools for different tasks.

With information on the web exponentially increasing, it has become more difficult than ever to navigate through everything to find reliable content that will help you get started with deep learning. This book is designed to help you if you’re a beginner looking to work on deep learning and build deep learning models from scratch, and already have the basic mathematical and programming knowledge required to get started.The book begins with a basic overview of machine learning, guiding you through setting up popular Python frameworks. You will also understand how to prepare data by cleaning and preprocessing it for deep learning, and gradually go on to explore neural networks. A dedicated section will give you insights into the working of neural networks by helping you get hands-on with training single and multiple layers of neurons. Later, you will cover popular neural network architectures such as CNNs, RNNs, AEs, VAEs, and GANs with the help of simple examples, and you will even build models from scratch. At the end of each chapter, you will find a question and answer section to help you test what you’ve learned through the course of the book.By the end of this book, you’ll be well-versed with deep learning concepts and have the knowledge you need to use specific algorithms with various tools for different tasks.