Add to ORKGIn recent times, computer scientists and technology companies have quickly begun to realize that machine learning and creating computer software that is capable of reasoning for itself (at least in theory). What was once only considered science fiction lore is now becoming a reality in front of our very eyes. With this type of computational capability at our disposal, we are left with the question of how best to use it and where to start in creating models that can help us best utilize it. TensorFlow is an open source software library used in machine learning developed and released by Google. It was created by the company in order to help them meet their expanding needs to train systems that can build and detect neural networks for pattern ...
Machine learning (ML) has become a powerful building block for modern services, scientific endeavors...
Deep learning powers many transformative core technologies including Autonomous Driving, Natural Lan...
In this article we exploit a combination of analytical and Machine Learning (ML) techniques in order...
Deep learning is a very computational intensive task. Traditionally GPUs have been used to speed-up ...
Machine learning is a rapidly growing field that has become more common of late. Because of the dema...
In recent years, deep-learning, a branch of machine learning gained increasing popularity due to the...
Deep neural networks have gained popularity in recent years, obtaining outstanding results in a wid...
Many state-of-the-art deep learning models rely on dynamic computation logic, making them difficult t...
Computational intensive applications such as pattern recognition, and natural language processing, a...
Machine Learning (ML) frameworks are tools that facilitate the development and deployment of ML mode...
Abstract : Deep learning is a part of artificial intelligence utilizing deep neural network architec...
Machine learning workflow development is a process of trial-and-error: developers iterate on workflo...
Deep neural networks have gained popularity in recent years, obtaining outstanding results in a wide...
Many machine learning algorithms iteratively process datapoints and transform global model parameter...
Research on distributed machine learning algorithms has focused pri-marily on one of two extremes—al...
Machine learning (ML) has become a powerful building block for modern services, scientific endeavors...
Deep learning powers many transformative core technologies including Autonomous Driving, Natural Lan...
In this article we exploit a combination of analytical and Machine Learning (ML) techniques in order...
Deep learning is a very computational intensive task. Traditionally GPUs have been used to speed-up ...
Machine learning is a rapidly growing field that has become more common of late. Because of the dema...
In recent years, deep-learning, a branch of machine learning gained increasing popularity due to the...
Deep neural networks have gained popularity in recent years, obtaining outstanding results in a wid...
Many state-of-the-art deep learning models rely on dynamic computation logic, making them difficult t...
Computational intensive applications such as pattern recognition, and natural language processing, a...
Machine Learning (ML) frameworks are tools that facilitate the development and deployment of ML mode...
Abstract : Deep learning is a part of artificial intelligence utilizing deep neural network architec...
Machine learning workflow development is a process of trial-and-error: developers iterate on workflo...
Deep neural networks have gained popularity in recent years, obtaining outstanding results in a wide...
Many machine learning algorithms iteratively process datapoints and transform global model parameter...
Research on distributed machine learning algorithms has focused pri-marily on one of two extremes—al...
Machine learning (ML) has become a powerful building block for modern services, scientific endeavors...
Deep learning powers many transformative core technologies including Autonomous Driving, Natural Lan...
In this article we exploit a combination of analytical and Machine Learning (ML) techniques in order...