SQL databases have constraints on data types and consistency. NoSQL does away with them for the sake of speed, flexibility, and scale

Data mining is the automated process of sorting through huge data sets to identify trends and patterns and establish relationships

Like yesterday’s data warehouses, today’s data lakes threaten to lock us into proprietary formats and systems that restrict innovation and raise costs

Analyzing large volumes of data is only part of what makes big data analytics different from traditional data analytics

A data lake can be a much more flexible repository than a data warehouse. Or it can be a trash dump that grows and grows

Intended to ease production deployments of PyTorch models, TorchServe supports multi-model serving and model versioning for A/B testing

TensorFlow, Spark MLlib, Scikit-learn, PyTorch, MXNet, and Keras shine for building and training machine learning and deep learning models

The past 12 months have revealed how valuable data science can be while also exposing its limitations. Expect big advances in the year to come.

The deep learning framework PyTorch has infiltrated the enterprise thanks to its relative ease of use.

Apple says the M1-compiled version of TensorFlow delivers several times faster performance on a number of benchmarks, while running existing TensorFlow scripts as-is