REST API Unified Architecture @Copyright -Image by Author

Introduction

The deployment of Machine Learning models is one of the key elements of the Data Science Process. Often Data Scientists struggles on the deployment part to expose the model as a seamless API that can be consumed by a number of endpoints. In this article, I will explain the architecture and design of the API — both on-prem and cloud. The most popular frameworks for Data Scientist are python-based Flask API server and Plumber for R users. We will explore how to use these frameworks in the production environment to make the API more robust, scalable, and fault-tolerant.

Platform as a service (PaaS) or On-prem servers

DSP+AI Workflow. @Copyright

The industrial plants consist of several types of assets. Sensor based IoT is employed for asset diagnostics and prognostics. The rotating parts of machine assets are often subjected to mechanical wear and tear. If monitoring is not done of this wear and tear, it may lead to the breakdown in the machines and unexpected shutdown in the plant. Apart from mechanical faults, machines can also develop electrical faults as well. Therefore, condition monitoring of these machines is very important for early stage fault detection to avoid unscheduled repairs, minimize downtime and hence, guarantee reliability, up-time, and sustainability of machines. Several…

Data Pipeline Architecture from Google Cloud Platform Reference Architecture

Introduction

In this article we will see how to configure complete end-to-end IoT pipeline on Google Cloud Platform. You will know -

How to create Device Registries in Cloud Iot Core

How to create Topics and Subscriptions

How to send messages to the device using GCP Python IoT Client

How to setup PubSub

How to setup Cloud Dataflow pipeline from PubSub to BigQuery

How to Setup Cloud IoT Core with Device Registeries and PubSub

Go to https://console.cloud.google.com/, login with your credentials and search for IoT Core.

After selecting IoT Core, its main interface page will open as below.

1. Introduction

In mathematics and science, a nonlinear system is a system in which the change of the output is not proportional to the change of the input. Nonlinear problems are of interest to engineers, biologists, physicists, mathematicians, and many other scientists because most systems are inherently nonlinear in nature. Nonlinear dynamical systems, describing changes in variables over time, may appear chaotic, unpredictable, or counterintuitive, contrasting with much simpler linear systems.

We are going to take the example of engineering systems that we intend to estimate the system model from a statistical/ML perspective. The design of engineering systems is done by the…

We focus on the scope of statistical science in the age where everything from mobiles, home -appliances and electronics, Cities, e-Commerce, Health Care, Connectivity to Industry 4.0 standard has become “smart”. Artificial Intelligence and Machine Learning are the new buzz word of technology; reminiscent to the discovery of electricity or invention of computers. Highest paid jobs are in AI, ML and Data Science. These avenues are not possible without statistical science at its core. …

Huzaifa Kapasi

Huzaifa Kapasi is Double MS Full time Res. from Warwick University. 15+ Years’ experience in Machine Learning, AI, big data, Cloud, Signal Processing Algorithms

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