Assignment 4: Chatbot
Assignment 4: Chatbot
Welcome to the last assignment of Course 4. Before you get started, we want to congratulate you on getting here. It is your 16t
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Assignment 3: Question Answering
Assignment 3: Question AnsweringWelcome to this week’s assignment of course 4. In this you will explore question answering. You will implement the “Te
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Transformer Summarizer
Assignment 2: Transformer SummarizerWelcome to the second assignment of course 4. In this assignment you will explore summarization using the transfor
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Using RL to Solve Blackjack
转载自: https://github.com/zht007/tensorflow-practice/blob/master/7_Renforcement_Learning_blackjack/强化学习——MC(蒙特卡洛)玩21点扑克游戏.md
1. 关于21点游戏1.1 规则简介21点的游戏规则详
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Generalized Policy Iteration
The key idea of DP, and of reinforcement learning generally, is the use of value functions to organize and structure the search for good policies. As
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Optimal Policies with Dynamic Programming
Assignment 2: Optimal Policies with Dynamic ProgrammingWelcome to Assignment 2. This notebook will help you understand:
Policy Evaluation and Policy
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Markov Decision Processes II
Lesson 1: Policies and Value FunctionsRecognize that a policy is a distribution over actions for each possible state.a policy is a mapping from states
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Markov Decision Processes I
Lesson 1: Introduction to Markov Decision ProcessesUnderstand Markov Decision Processes, or MDPsMDPs are a classical formalization of sequential decis
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The K-Armed Bandit Problem
Lesson 1: The K-Armed Bandit ProblemDefine rewardIn the k-armed bandit problem, each of the k actions has an expected or mean reward given that that a
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Bandits and Exploration/Exploitation
Assignment 1: Bandits and Exploration/ExploitationWelcome to Assignment 1. This notebook will:
Help you create your first bandit algorithm
Help you u
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