Artificial Intelligence | News, analysis, features, how-tos, and videos
Having data scientists collaborate with devops and engineers leads to better business outcomes, but understanding their different requirements is key
TensorFlow, Spark MLlib, Scikit-learn, PyTorch, MXNet, and Keras shine for building and training machine learning and deep learning models.
No-code connectors to Azure Cognitive Services make it easy to get started with artificial intelligence
Now more platform than toolkit, TensorFlow has made strides in everything from ease of use to distributed training and deployment
Train and evaluate a simple time series model using a random forest of regression trees and the NYC Yellow taxi data set.
Supervised learning turns labeled training data into a tuned predictive model
Google’s TensorFlow 2.0 is now available in beta, with a focus on improving performance, ease, compatibility, and continuity
As AI becomes more prevalent, organizations must make it easier for developers to unlock AI’s potential
Reinforcement learning uses rewards and penalties to teach computers how to play games and robots how to perform tasks independently
Deep learning has improved machine translation and other natural language processing tasks by leaps and bounds