Deep learning is an AI function and a subset of machine learning, used for processing large amounts of complex data. Deep learning can automatically create algorithms based on data patterns. Here are 4,600 public repositories matching this topic... Language: All Sort: Most stars deepfakes ...
Top Deep Learning Projects Everyone has projects in their university life. The project may be small or revolutionary. It is very natural for one to work on Deep Learning as it isan age of Artificial Intelligence and Machine Learning. But one may get confused by a lot of options. So, we h...
Deep Lattice Networks and Partial Monotonic Functions [Research at Google] [article] [code] The IIT Bombay English-Hindi Parallel Corpus [arXiv] [article] Rainbow: Combining Improvements in Deep Reinforcement Learning [arXiv] Lifelong Learning With Dynamically Expandable Networks [arXiv] Variational In...
How can I get you proficient with deep learning for computer vision as fast as possible?The Machine Learning Mastery method suggests that the best way of learning this material is by doing. This means the focus of the book is hands-on with projects and tutorials. This also means not ...
《Randy Olson's data analysis and machine learning projects》 介绍:Randy Olson's的一些数据分析与机器学习项目库,是学习实践的好材料 《GoLearn:Golang machine learning library》 介绍:Golang机器学习库,简单,易扩展 《Swift Ai》 介绍:用Swift开发苹果应用的倒是很多,而用来做机器学习的就比较少了.Swift Ai...
Deep research was trained using end-to-end reinforcement learning on hard browsing and reasoning tasks across a range of domains. Through that training, it learned to plan and execute a multi-step trajectory to find the data it needs, backtracking and reacting to real-time information where nece...
(Physics) and in Computer Science and Technology. His research interests includedeep reinforcement learning, robotics, computer vision, quantum computation and machine learning. He has published papers in ICRA, AAAI, NIPS, IJCAI, and Physical Review. He also contributed to the open-source projects ...
In this section we first clarify some general concepts and terms relevant for anomaly detection in log data based on deep learning. We then outline scientific challenges that are specific to that research field. 2.1. Preliminary definitions The study carried out in this paper hinges on an understa...
3.5.6. Transfer Learning Surveyjindongwang/transferlearning: Transfer learning / domain adaptation / domain generalization / multi-task learning etc. papers, codes. datasets, applications, tutorials.-迁移学习 3.5.7. Neural Tangent Python: google/neural-tangents: Fast and Easy Infinite Neural Networks...
We provide an overview of these DL tools and discuss how they may be applied to the analysis of genetic data for epilepsy research. Keywords: machine learning; deep learning; genetic epilepsy; non-protein-coding; omics data integration1. Introduction Affecting approximately one percent of the ...