deep learning coursera github

Deep Learning SpecializationWunda recently launched a series of courses on deep learning in Coursera with Deeplearning.ai, which is more practical compared to the previous machine learning course. The operating language also has M

This section mainly introduces a deep learning MATLAB version of the Toolbox, Deeplearntoolbox The code in the Toolbox is simple and feels more suitable for learning algorithms. There are common network structures, including deep networks (NN), sparse self-coding networks (SAE), CAE, depth belief networks (DBN) (based

Bengio, LeCun, Jordan, Hinton, Schmidhuber, Ng, de Freitas and OpenAI had done Reddit AMA's. These is nice places-to-start to get a zeitgeist of the field.Hinton and Ng lectures at Coursera, UFLDL, cs224d and cs231n at Stanford, the deep learning course at udacity, and the sum Mer School at IPAM has excellent tutorials, video lectures and programming exercises th

to convert it into a practical problem. We are now people to see, to locate the problem, the amount of labor is very large, what machine learning method? 2. What are the algorithm recommendations besides the correlation analysis algorithm? 3. After we have to do long text, relevance analysis algorithm is appropriate? Do you have any algorithm suggestions? A : understand, that can actually be converted into a text classification problem, your input is

Ng's machine learning courses on Coursera are the best choice for getting started. In addition, Yaser Abu-mostafa's machine learning program is more focused on theory, but also suitable for beginners. Learning deep learning does

connected), million parameters, rectified Linear Units (relus) , Local Response Normalization, dropoutVggOriginal paper: "Very deep convolutional Networks for large-scale Image recognition" [arxiv]Properties:19 weight layers, 144m parameters, 3x3 convolution filters, L2 regularised, dropout, No Local Response Normali ZationGooglenetOriginal paper: "going deeper with convolutions" [arxiv]Lates upgrade to the model achieves even better scores with mode

despair. His style of being alone has influenced my view of the whole Tibetan minority, and there is no place to respect it. I thought, "I don't think I slept again tonight." ”I just climb out of bed straight start open source work, document open-source to GitHub a lot of ways, direct use of GitHub Markdown is too humble, the file organization is not beautiful, a website alone and some too. At the end, tak

Deep learning has been fire for a long time, some people have been here for many years, and some people have just begun, such as myself. How to get into this field quickly in a short period of time to master deep learning the latest technology is a question worth thinking about. In the present situation, it is the best

Chinese books. But "machine learning", "statistical learning method" is still worth a look. Foreign language Recommendation "Pattern Recognition and machine learning" and "Machine learning:a Probabilistic Perspective", the latter containing the chapters of the Deep Neural network。 3.