Top 5 Sentiment Analysis Example

The term sentiment analysis is quite popular. But most people do not really notice how important it is for a company’s success. Sentiment analysis provides an insight into all the problems that your company may be facing. It is like being able to listen to all the conversations that your customers are having about your product. It helps you understand how your brand is being perceived and work towards improving its image based on those insights.

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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 art Sentiment Analysis Algorithms

Introduction to Sentiment Analysis

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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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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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10 Stunning Applications of AI in Retail

Here are 10 stunning applications of AI in retail that you might not be aware of. The retail sector is under heavy pressure due to increasing customer demands and cutthroat competition. To face such heavy demands, AI can lend a helping hand to retailers. Major retailers like Lowes, Target, Amazon are increasing their AI spend to improve their customer experience, bring in more sales, profitability, process efficiency and cost savings.

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Top 4 Natural Language Processing Applications for Businesses

Natural Language Processing (NLP) has become more than an emerging technology. It has multiple applications in businesses today and is being widely used in various industries. NLP tools understand the meaning and context of phrases and provides automated support. They can be incorporated in any feature involving language, including online search, extract meaning, generate text, summarize a long document, or detect spam email.

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Data Labeling Platform - Skyl

Skyl's data labeling platform allows you to quickly annotate and label data to suit your machine learning needs.

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What is Data Labeling in machine learning?

When you are embarking on a machine learning project, data labeling is one of the key components that will determine the success of the project. One of the important steps in machine learning projects (especially in unsupervised methods) is data labeling which is a process of augmenting raw data with a set a meaningful tags.

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How Banks can Leverage Deep Learning

As the user base and number of transactions per day keeps on increasing in the banking sector, top banking CIOs are constantly on the look out for new technologies that can help in running their banks better and smarter.

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