Search results for "Recurrent Neural Networks"
-
6 areas of AI and Machine Learning to watch closely">
Artificial Intelligence is a generic term and many fields of science overlaps when comes to make an AI application. Here is an explanation of AI and its 6 major areas to be focused, going forward.
6 areas of AI and Machine Learning to watch closely
https://www.kdnuggets.com/2017/01/6-areas-ai-machine-learning.html
-
Multi-Task Learning in Tensorflow: Part 1
A discussion and step-by-step tutorial on how to use Tensorflow graphs for multi-task learning.https://www.kdnuggets.com/2016/07/multi-task-learning-tensorflow-part-1.html
-
5 Deep Learning Projects You Can No Longer Overlook
There are a number of "mainstream" deep learning projects out there, but many more niche projects flying under the radar. Have a look at 5 such projects worth checking out.https://www.kdnuggets.com/2016/07/five-deep-learning-projects-cant-overlook.html
-
The Amazing Power of Word Vectors
A fantastic overview of several now-classic papers on word2vec, the work of Mikolov et al. at Google on efficient vector representations of words, and what you can do with them.https://www.kdnuggets.com/2016/05/amazing-power-word-vectors.html
-
New Deep Learning Book Finished, Finalized Online Version Available
What will likely become known as the seminal book on deep learning is finally finished, with the online version finalized and freely-accessible to all those interested in mastering deep neural networks.https://www.kdnuggets.com/2016/04/deep-learning-book-finished.html
-
Scikit Flow: Easy Deep Learning with TensorFlow and Scikit-learn">
Scikit Learn is a new easy-to-use interface for TensorFlow from Google based on the Scikit-learn fit/predict model. Does it succeed in making deep learning more accessible?
Scikit Flow: Easy Deep Learning with TensorFlow and Scikit-learn
https://www.kdnuggets.com/2016/02/scikit-flow-easy-deep-learning-tensorflow-scikit-learn.html
-
AI Supercomputers: Microsoft Oxford, IBM Watson, Google DeepMind, Baidu Minwa
In the world of AI, this is the equivalent of the US and USSR competing to put their guy on the moon first. Here is a profile of some of the giants locked into the AI space race.https://www.kdnuggets.com/2016/02/ai-supercomputers-microsoft-ibm-watson-google-deepmind-baidu.html
-
Research Leaders on Data Mining, Data Science and Big Data key advances, top trends
Research Leaders in Data Science and Big Data reflect on the most important research advances in 2015 and the key trends expected to dominate throughout 2016.https://www.kdnuggets.com/2016/01/research-leaders-data-science-big-data-top-trends.html
-
50 Deep Learning Software Tools and Platforms, Updated
We present the popular software & toolkit resources for Deep Learning, including Caffe, Cuda-convnet, Deeplearning4j, Pylearn2, Theano, and Torch. Explore the new list!https://www.kdnuggets.com/2015/12/deep-learning-tools.html
-
A Statistical View of Deep Learning
A statistical overview of deep learning, with a focus on testing wide-held beliefs, highlighting statistical connections, and the unseen implications of deep learning. The post links to 6 articles covering a number of related topics.https://www.kdnuggets.com/2015/11/statistical-view-deep-learning.html
-
MetaMind Mastermind Richard Socher: Uncut Interview
In a wide-ranging interview, Richard Socher opens up about MetaMind, deep learning, the nature of corporate research, and the future of machine learning.https://www.kdnuggets.com/2015/10/metamind-mastermind-richard-socher-deep-learning-interview.html
-
KDnuggets™ News 14:n27, Oct 22
Features | Software | Opinions | Interviews | Reports | News | Webcasts | Courses | Meetings | Jobs | Academic | Publications | Tweets Read more »https://www.kdnuggets.com/2014/n27.html
-
Software Suites/Platforms for Analytics, Data Mining, Data Science, and Machine Learning
commercial | free/open source A B C D E F G H I J K L M N O PQ R S T U V Read more »https://www.kdnuggets.com/software/suites.html
6 areas of AI and Machine Learning to watch closely
Scikit Flow: Easy Deep Learning with TensorFlow and Scikit-learn