Displaying 1 to 7 from 7 results

interactive-deep-colorization - Deep learning software for colorizing black and white images with a few clicks

  •    Jupyter

We first describe the system (0) Prerequisities and steps for (1) Getting started. We then describe the interactive colorization demo (2) Interactive Colorization (Local Hints Network). There are two demos: (a) a "barebones" version in iPython notebook and (b) the full GUI we used in our paper. We then provide an example of the (3) Global Hints Network. We provide a "barebones" demo in iPython notebook, which does not require QT. We also provide our full GUI demo.

colorization - Automatic colorization using deep neural networks

  •    Jupyter

Richard Zhang, Phillip Isola, Alexei A. Efros. In ECCV, 2016. This code requires a working installation of Caffe and basic Python libraries (numpy, pyplot, skimage, scipy). For guidelines and help with installation of Caffe, consult the installation guide and Caffe users group.

Hands-On-Reinforcement-Learning-With-Python - Master Reinforcement and Deep Reinforcement Learning using OpenAI Gym and TensorFlow

  •    Jupyter

Reinforcement Learning with Python will help you to master basic reinforcement learning algorithms to the advanced deep reinforcement learning algorithms. The book starts with an introduction to Reinforcement Learning followed by OpenAI and Tensorflow. You will then explore various RL algorithms and concepts such as the Markov Decision Processes, Monte-Carlo methods, and dynamic programming, including value and policy iteration. This example-rich guide will introduce you to deep learning, covering various deep learning algorithms. You will then explore deep reinforcement learning in depth, which is a combination of deep learning and reinforcement learning. You will master various deep reinforcement learning algorithms such as DQN, Double DQN. Dueling DQN, DRQN, A3C, DDPG, TRPO, and PPO. You will also learn about recent advancements in reinforcement learning such as imagination augmented agents, learn from human preference, DQfD, HER and many more.




ladder - Ladder network is a deep learning algorithm that combines supervised and unsupervised learning

  •    Python

This is an implementation of Ladder Network in TensorFlow. Ladder network is a deep learning algorithm that combines supervised and unsupervised learning. It was introduced in the paper Semi-Supervised Learning with Ladder Network by A Rasmus, H Valpola, M Honkala, M Berglund, and T Raiko.

Reinforcement-Learning - 🤖 Implements of Reinforcement Learning algorithms.

  •    Python

This repo is implements of Reinforcement Learning Algorithms, implementing as learning, some of them are even another version of some tutorial. Any contributions are welcomed. Deep Deterministic Policy Gradient (DDPG) Implement of DDPG.