Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Ramya Krishnamoorthy shares a detailed case ...

TensorFlow, Spark MLlib, Scikit-learn, PyTorch, MXNet, and Keras shine for building and training machine learning and deep learning models. If you’re starting a new machine learning or deep learning ...

Machine learning is a complex discipline but implementing machine learning models is far less daunting than it used to be. Machine learning frameworks like Google’s TensorFlow ease the process of ...

Teaching yourself deep learning is a long and arduous process. You need a strong background in linear algebra and calculus, good Python programming skills, and a solid grasp of data science, machine ...

Over the past year I’ve reviewed half a dozen open source machine learning and/or deep learning frameworks: Caffe, Microsoft Cognitive Toolkit (aka CNTK 2), MXNet, Scikit-learn, Spark MLlib, and ...

Python libraries that can interpret and explain machine learning models provide valuable insights into their predictions and ensure transparency in AI applications. A Python library is a collection of ...

AI and deep learning are pretty hot technologies right now, what with the accelerating interest in computer vision, image recognition and classification, natural language processing (NLP), and speech ...

Machine Learning (ML) stands as one of the most revolutionary technologies of our era, reshaping industries and creating new frontiers in data analysis and automation. At the heart of this ...

Machine learning is an integral part of what powers our online existences. It’s the technology that helps suggest new Facebook friends and impulse purchases on Amazon. And also a field that Google, ...

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More At Google’s inaugural TensorFlow Dev Summit in Mountain View, California, ...