Neural Networks for Machine Learning, Coursera上的著名课程,由Geoffrey Hinton教授主讲。 Stanford CS 229, Andrew Ng机器学习课无阉割版,Notes比较详细 CMU 10-702 Statistical Machine Learning, 讲师是Larry Wasserman,应该是统计系开的机器学习,非常数学化,第一节课就提到了RKHS(Reproducing Kernel Hilbert Space...
Neural Networks for Machine Learning, Coursera上的著名课程,由Geoffrey Hinton教授主讲。 Stanford CS 229, Andrew Ng机器学习课无阉割版,Notes比较详细,可以对照学习CS229课程讲义的中文翻译。 CMU 10-702 Statistical Machine Learning, 讲师是Larry Wasserman,应该是统计系开的机器学习,非常数学化,第一节课就提到了...
Machine Learning - Oxford(2014-2015) Deep Learning - Nvidia(2015) Graduate Summer School: Deep Learning, Feature Learningby Geoffrey Hinton, Yoshua Bengio, Yann LeCun, Andrew Ng, Nando de Freitas and several others @ IPAM, UCLA (2012) Deep Learning - Udacity/Googleby Vincent Vanhoucke and Arp...
Machine Learning - Oxford(2014-2015) Deep Learning - Nvidia(2015) Graduate Summer School: Deep Learning, Feature Learningby Geoffrey Hinton, Yoshua Bengio, Yann LeCun, Andrew Ng, Nando de Freitas and several others @ IPAM, UCLA (2012) Deep Learning - Udacity/Googleby Vincent Vanhoucke and Arp...
原文连接:http://www.kdnuggets.com/2016/11/top-20-python-machine-learning-open-source-updated.html 28款GitHub最流行的开源机器学习项目 现在机器学习逐渐成为行业热门,经过二十几年的发展,机器学习目前也有了十分广泛的应用,如:数据挖掘、计算机视觉、自然语言处理、生物特征识别、搜索引擎、医学诊断、DNA序列测序...
5. Resources of NIPS 2017 2. 开源工具 1. TensorFlow 2. TuriCreate – A Simplified Machine Learning Library 3. OpenPose 4. DeepSpeech 5. Mobile Deep Learning 6. Visdom 7. Deep Photo Style Transfer 8. CycleGAN 9. Seq2seq 10. Pix2code ...
Machine learning and AI integration LLMs are grounded in machine learning and artificial intelligence principles. They're neural networks with millions, or even billions, of parameters that are fine-tuned during the training process to understand and predict text effectivel...
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19.Python 学习机器样品 www.github.com/awslabs/machine-learning-samples 用亚马逊的机器学习建造的简单软件收集。 20.Python-ELM www.github.com/dclambert/Python-ELM 这是一个在Python语言下基于scikit-learn的极端学习机器的实现。 在这样的背景下, InfoWorld近日公布了机器学习领域11个最受欢迎的开源项目,这...
apachecn / AiLearning AiLearning: 机器学习 - MachineLearning - ML、深度学习 - DeepLearning - DL、自然语言处理 NLP。网站: http://ailearning.apachecn.org scutan90 / DeepLearning-500-questions 深度学习500问,以问答形式对常用的概率知识、线性代数、机器学习、深度学习、计算机视觉等热点问题进行阐述。