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L1 Machine Learning to Deep Learning Subtitles
- Deep learning for machine learning aspirants
object-detection-deep-learning
- deep learning object identification and trcaking
deep learning中文版
- 深度学习，中文版，这本书比较详细的讲解了深度学习相关的知识(Deep learning (also known as deep structured learning or hierarchical learning) is part of a broader family of machine learning methods based on learning data representations, as opposed to task-specific algorithms. Lear
Apress.MATLAB.Deep.Learning.1484228448
- deep learning with matlab
Deep Learning OpenCV
- Deep Learning OpenCV This pdf is about Deep Learning Opencv.
Wide & Deep Learning for Recommender Systems
- Wide & Deep Learning for Recommender Systems
MATLAB Deep Learning (1)
- Deep learning book using matlab
Deep Learning BOOK(Bengio)
- Yoshua Bengio编写的深度学习书籍，详细介绍了深度学习的各方面内容，此版本为英文版(The deep learning book, written by Yoshua Bengio, describes in detail all aspects of deep learning. This version is in English.)
Mathematical Aspects of Deep Learning
- 深度学习需要用到的数学方法。。。。。。。(Deep learning mathematics used)
Deep Learning with Python-Manning
- 深入学习Python介绍领域的深入学习使用Python语言和强大的Keras图书馆。通过keras创造者和谷歌人工智能研究者弗兰?ois Chollet写的，这本书让你了解通过直观的解释和实例。您将探索具有挑战性的概念和实践与计算机视觉，自然语言处理和生成模型的应用程序。当你完成学业的时候，你将具备在自己的项目中应用深度学习的知识和动手能力。(Deep Learning with Python introduces the field of deep learning using the Pyt
Pro Deep Learning with TensorFlow
- Pro Deep Learning with TensorFlow
Deep Learning Papers Reading Roadmap
- 这是一些关于深度学习的基础资料，希望对一些初学者有帮助!(These are some basic materials about deep learning, hope they are helpful to beginners!)
Deep Learning Papers Reading Roadmap
- 这是一些关于深度学习的一些入门资料，希望对初学者有帮助！(These are some basic materials about deep learning, hope helpful to these beginners!)
Deep Learning Papers Reading Roadmap
- 这是一些关于深度学习的入门资料，希望对初学者有些帮助。(These are some basic materials on deep learning, hope they are helpful to the beginners!)
Deep Learning
- 深度学习（deep learning）英文专著，适合深度学习的理论基础学习。(A monographs which suitable for the theoretical basis of deep learning.)
Deep Learning Based Communication Over the Air
- 通信系统的端到端学习是a 引人入胜的新颖概念迄今为止仅被验证 模拟基于块的传输。它允许学习 发射机和接收机实现为深度神经网络 （NN），它们针对任意可区分的端到端进行了优化 performancemetric，例如块错误率（BLER）。在本文中，我们 证明无线传输是可能的：我们建造， 训练，并运行完整的通讯系统 的神经网络使用非同步的现成软件定义无线电 和开源深度学习软件库。(End-to-end learning of communications systems is a
stanford-deep-learning-matlab-code
- Stanford 大学的深度学习源代码，可用于模式识别和预测，比较稳定。(Stanford University's deep learning source code can be used for pattern recognition and prediction, and is relatively stable.)
Deep Learning with Python
- 本书由Keras之父、现任Google人工智能研究员的弗朗索瓦?肖莱（Fran?ois Chollet）执笔，详尽介绍了用Python和Keras进行深度学习的探索实践，涉及计算机视觉、自然语言处理、生成式模型等应用。书中包含30多个代码示例，步骤讲解详细透彻。由于本书立足于人工智能的可达性和大众化，读者无须具备机器学习相关背景知识即可展开阅读。在学习完本书后，读者将具备搭建自己的深度学习环境、建立图像识别模型、生成图像和文字等能力。(Deep Learning with Python intr
Neural-Networks-and-Deep-Learning-A-Textbook
- Charu C. Aggarwal Neural Networks and Deep Learning
2016-deep learning
- deep learning英文电子版pdf，深度学习不错的书籍(Deep learning English electronic PDF, good books for deep learning)