Enterprise-class organizations across all industries are looking to embrace artificial intelligence (AI). They are beginning to recognize the game-changing and transformative benefits they can attain with AI—and they need to arm their data science teams with the tools and data to drive innovation and business value with machine learning (ML) and deep learning (DL). Data science teams want to leverage their preferred frameworks (TensorFlow, PyTorch, Theano, Caffe2, etc.); learning algorithms (decision trees, Naive Bayes, random forest, XGBoost, etc.); and applications and tools (Jupyter notebooks, RStudio Server, AutoML, H2O.ai, Dataiku, etc.) to develop their models—from data selection and training, to model deployment.
