How to Build a Twitter Sentiment Analysis Tool using Skyl.ai

Hundreds of millions of people willingly spew their opinions in under 280 characters per post and 6,000 times per second. Sentiment analysis on social media platforms such as Twitter is a very effective way for analysts to gauge consumer reactions to products and services. The use of machine learning is necessary to properly gather consumer reactions. Individuals sifting through tweets ranging from “Where the Buffalo Wild Things Are” to firey, researched political statements can easily get in the noise and twitter void, especially if a business just wants to gauge the attitude towards a particular product or service.

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Learn About State of the Art Sentiment Analysis Algorithms

Introduction to Sentiment Analysis

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Why Is Content Moderation Important for an Online Business?

With increasing competition, online businesses are finding it hard to thrive. They need more creative marketing techniques to attract consumers. User-generated content is one such technique that is becoming the most powerful marketing tool used by online businesses today.  

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How Does Content Moderation Using AI work?

With the advent of the internet, it has never been easier than it is now to publish content. Anyone with a smart device and a web-connection can publish on a multitude of platforms catered for that specific purpose. In recent years, a global debate has emerged around the risks faced by internet users, with a specific focus on protecting users from harmful content. A key element of this debate has centered on the role of content moderation to protect users from potentially harmful material. 

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Understanding Deep Learning Algorithms for Named Entity Recognition: Skyl.ai

What is Named Entity Recognition (NER)

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Build a Named Entity Recognition (NER) ML model in hours

Named-entity recognition (NER) also known as entity extraction is a subtask of information extraction that aims to locate and classify atomic elements in text into predefined categories such as the names of persons, organizations, places, expressions of times, quantities, monetary values and more.

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Computer Vision Advantages and Disadvantages

Artificial intelligence encompasses several different approaches to solving problems. Computer vision, object detection, natural language processing, and other types of artificial intelligence help businesses and individuals automate processes, improve accuracy, and work more efficiently. The subset of AI known as computer vision centers around visual processing and offers benefits in a range of applications. 

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What is Topic Modeling? An Introduction to Topic Modeling Use Cases

Imagine that you need to find a specific piece of information for your company, from a large collection of documents, within a tight deadline. It may be an important statistic or a crucial piece of information needed urgently. How much time do you think it will take for you to find that information from your company database? Looking for information within millions of documents will be like looking for a needle in a haystack. It will take a long time and the task will be practically impossible. This is where Machine learning and Topic modeling comes into place.

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When Do You Need AI Consulting?

There’s a lot of buzz about artificial intelligence (AI) and the many benefits it offers to the organizations that use it. Most recently, AI has been leveraged in the healthcare industry in response to the global pandemic for mapping, to accelerate diagnoses, and to predict health outcomes. Although the technology is not brand-new (it has been around since the 1950s), the concept of AI still feels inaccessible to many.

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Understanding 3 Types of Machine Learning Algorithms

Machines learn through algorithms—sets of rules or instructions—that allow them to continually improve through experience. In contrast to programming, which can tell a machine to do a specific task in the same way over and over, machine learning algorithms modify themselves over time based on the original goal set and previous results. 

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