Evaluating GANs
Evaluating GANsGoalsIn this notebook, you’re going to gain a better understanding of some of the challenges that come with evaluating GANs and a respo
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Build a Conditional GAN
Build a Conditional GANGoalsIn this notebook, you’re going to make a conditional GAN in order to generate hand-written images of digits, conditioned o
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Wasserstein GAN with Gradient Penalty (WGAN-GP)
Wasserstein GAN with Gradient Penalty (WGAN-GP)GoalsIn this notebook, you’re going to build a Wasserstein GAN with Gradient Penalty (WGAN-GP) that sol
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Deep Convolutional GAN (DCGAN)
Deep Convolutional GAN (DCGAN)GoalIn this notebook, you’re going to create another GAN using the MNIST dataset. You will implement a Deep Convolutiona
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Your First GAN
Your First GANGoalIn this notebook, you’re going to create your first generative adversarial network (GAN) for this course! Specifically, you will bui
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Dyna-Q and Dyna-Q+
Assignment: Dyna-Q and Dyna-Q+Welcome to this programming assignment! In this notebook, you will:
implement the Dyna-Q and Dyna-Q+ algorithms.
compa
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Planning and learning with Tabular Methods
We develop a unified view of reinforcement learning methods that require a model of the environment, such as dynamic programming and heuristic search,
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Q-Learning and Expected Sarsa
Assignment 2 - Q-Learning and Expected SarsaWelcome to Course 2 Programming Assignment 2. In this notebook, you will:
Implement Q-Learning with $\eps
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Policy Evaluation in Cliff Walking Environment
Assignment: Policy Evaluation in Cliff Walking EnvironmentWelcome to the Course 2 Module 2 Programming Assignment! In this assignment, you will implem
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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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