AI Platforms in 2020: Guide to ML life cycle support tools

Research indicates that organizations have a hard time productizing machine learning models. AI platforms help businesses build, manage and deploy machine learning and deep learning models at scale. It makes AI technology more attainable and affordable by reducing software development work such as data management and deployment.

What is an AI platform?

An AI platform is a set of services that support the machine learning life cycle. This includes support for gathering and preparing data as well as training, testing, and deploying machine learning models for applications at scale. Read more

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Data labeling/ annotation/ classification in 2020: In-depth Guide

Since 2010s, companies have been heavily investing in machine learning. Supervised learning is the most common form of machine learning today. Supervised learning algorithms need to be fed with labeled instances. This increases the importance of data labeling solutions.

Therefore, data labeling tools (open source vs proprietary), service providers and alternatives to data labeling are important aspects of a company’s data labeling strategy:

What is data labeling?

Supervised machine learning algorithms learn from labeled data, data that has been tagged with labels. Programmers do not explicitly program machine learning algorithms on how to make decisions, they program the models that learn from labeled data. Read more

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Enterprise Search 2020: In-Depth Guide

Enterprise search is a valuable tool for businesses since it allows employees to perform instant searches within the company’s knowledge base. This decreases the amount of time it takes for an employee to find the necessary information, leaving more time for higher value-added tasks.

We answered all your enterprise search-related questions:

What is an enterprise search?

Enterprise search is a way of search that helps employees find the data from one or multiple databases in a single search query. The searched data can be, in any format, from anywhere inside the company -in databases, document management systems, e-mail servers, on paper and so on. Read more

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Application Analytics 2020: In-Depth Guide

Though the number of applications is increasing, the number of successful applications remains limited. Application analytics solutions capture and analyze application metrics such as usage patterns. Insights from application analytics enable companies to continuously improve their cloud, desktop and mobile applications. Benchmarking and tracking a relevant set of metrics which we provide below enables companies to have an edge in application analytics

What is application analytics?

Application analytics is the collection of data, real-time analysis and reporting of application usage patterns. It covers analytics in mobile, desktop, and other device applications. It can be used to gain insights into IT operations, customer experience and business outcomes. Read more

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Cognitive Analytics = Analytics with AI: In-Depth Guide

Cognitive Analytics is the last generation of Analytics

Data analytics has evolved over the past few decades from descriptive to prescriptive analytics. A new analytics era has begun along with AI technology. Organizations are using AI capabilities such as machine learning, natural language processing and computer vision so enterprises gain insights and make data-driven decisions.

Some common questions related to cognitive analytics that we cover in this post include:

What is Cognitive Analytics?

Cognitive Analytics is a technology that uses advanced analytics to analyze larger and more complex data sets. In short, it is AI applied to analytics. Read more

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