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Snowflake is an analytic data warehouse provided as Software-as-a-Service (SaaS). The Snowflake data warehouse uses a new SQL database engine with a unique architecture designed for the cloud and provides a data warehouse that is faster, easier to use, and far more flexible than traditional data warehouse offerings.
DGX is a workstation made by NVIDIA, that specializes in GPU acceleration for deep learning applications. DGX is optimized for accelerated data loading, data manipulation, and training of algorithms, get faster insights leveraging the performance and large GPU memory footprint of NVIDIA DGX Station.
An on-premise server is a physical, on-site server that a company must manage and maintain individually. While sometimes more costly in the short term, on premises is often considered more secure and reliable.
Apache Spark is an open source general purpose cluster-computing framework. Spark provides an interface for programming entire clusters with implicit data parallelism and fault tolerance. Spark includes a framework called MLlib for machine learning
Red Hat® OpenShift® is an enterprise-ready Kubernetes container platform with full-stack automated operations to manage hybrid cloud and multicloud deployments. Red Hat OpenShift is optimized to improve developer productivity and promote innovation.
VMware Enterprise PKS is a Kubernetes-based container solution with advanced networking, a private container registry, and life cycle management. Enterprise PKS simplifies the deployment and operation of Kubernetes clusters so you can run and manage containers at scale on private and public clouds.
Google Cloud Platform, offered by Google, is a suite of cloud computing services that runs on the same infrastructure that Google uses internally for its end-user products such as, Google Search, Gmail and YouTube.
Microsoft Azure is a cloud computing service created by Microsoft for building, testing, deploying, and managing applications and services through Microsoft-managed data centers.
K Nearest Neighbors is a classic algorithm for classification and regression. The algorithm receives the natural number K as an input and a training set. During the test set, for each sample the algorithm checks the K’s closest elements in the training set to the sample and classify it by a “plurality vote”.
Recurrent Neural Network is a class of neural networks where connections between nodes form a directed graph along a temporal sequence. In this type of network, a cycle can be formed and this behavior allows the creation of “internal memory” in order to process sequences of inputs. This makes them applicable to tasks such as handwriting recognition or speech recognition.
Support Vector Machine (SVM) is a supervised learning model. The SVM model is a representation of the examples as points in space, mapped so that the examples of the separate categories are divided by a clear gap that is as wide as possible. New examples are then mapped into that same space and predicted to belong to a category based on the side of the gap on which they fall.
Random forests or random decision forests are an ensemble learning method for classification, regression and other tasks that operate by constructing a multitude of decision trees at training time and outputting the class that is the mode of the classes or mean prediction of the individual trees.
Logistic Regression is an ML algorithm which is used for classification problems, it is a predictive analysis algorithm based on the concept of probability. The algorithm classifies with the sigmoid function which always returns values between 0 (absolutely false) and 1 (absolutely true).
XGBoost is an open-source software library which provides a gradient boosting framework for C++, Java, Python, R, Julia, Perl, and Scala.
K-Means is a clustering algorithm. This algorithm aims to cluster the data to K groups (clusters) such that each example in the data is as close as possible to the nearest centroid.