This guide is for those who know some math, know some programming language and now want to dive deep into deep learning
In summary, this project seeks to explore the science behind Neural Networks (NN), its various flavours, application areas and then finally, narrow down by applying it in the design and development of a computer vision system which can be used for traffic sign recognition and detection in autonomous vehicles. The project starts off by designing, developing, implementing and testing a model of the proposed vision system on a CPU using MATLAB and then afterwards, the performance of the implemented vision system is further optimized through vectorization, parallelism, legacy coding and heterogeneous computing. The project is concluded with detailed analysis and evaluation of the various optimization schemes utilized as well as an evaluation of the excellent Neural Network’s classification accuracy.
Learn image classification and language modeling
Hands-On Deep Learning for Computer Vision [Video], by Packt Publishing
A library for encrypted, privacy preserving machine learning
A list of ICs and IPs for AI, Machine Learning and Deep Learning.
Distributed Deep learning with Keras & Spark
A curated list of awesome Deep Learning tutorials, projects and communities.
This is the code package related to the follow scientific article: Luca Sanguinetti, Alessio Zappone, Merouane Debbah 'Deep-Learning-Power-Allocation-in-Massive-MIMO' presented at the Asilomar Conference on Signals, Systems, and Computers, 2018. http://www.asilomarsscconf.org
AiAi.care project is teaching computers to "see" chest X-rays and interpret them how a human Radiologist would. We are using 700,000 Chest X-Rays + Deep Learning to build an FDA approved, open-source screening tool for Tuberculosis and Lung Cancer. After an MRMC clinical trial, AiAi CAD will be distributed for free to emerging nations, charitable hospitals, and organizations like WHO We will also release our pretrained models and weights as Medical Imagenet.