Guide to Understand Text Classification and Its Use Cases

Data is growing day by day, at a speed and power never seen before, making it important to have easier ways of finding information. With this range of knowledge available, it is essential to find the right information at the right time. Text classification helps us to do exactly that.

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85% of Machine Learning Projects Fail! Here’s How Yours May Actually Succeed

Only 15% of Machine learning projects succeed, or 1 out of every 10 make it to production. 55% of machine learning projects are not even completed. And, only 8% of AI projects are regarded as ‘very’ successful. These are some staggering statistics begging to be noticed by all the organizations out there aiming to launch an effective and bankable ML project.

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Common Misconceptions About Data Labeling and Classification

Just like human students need teachers to help them understand educational material, machines require more than just raw data to learn. Data labeling is a key component of a successful machine learning project, but unfortunately, there are some common misconceptions about its importance, how it is done, and who can do it. 

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Artificial Intelligence vs. Machine Learning (AI vs ML)? And What’s the Difference?

Artificial intelligence (AI) and machine learning (ML) are two terms that are coming to the forefront. More organizations are adopting these new technologies, which are now all around us but not always immediately visible. Businesses with e-commerce sites are taking advantage of the ability to increase sales by recommending products based on product images viewed. The healthcare industry is treating patients faster because machines can recognize patterns in high-resolution medical imagery. Manufacturers are improving quality control and catching small errors before they become major issues. 

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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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Twitter Sentiment Analysis Using Machine Learning

Natural Language Processing (NLP) is a popular technology for research and data collection, and sentiment analysis is one of the most common sub-fields of NLP. Sentiment Analysis is the process of analyzing online pieces of writing to predict their emotional tone, i.e. whether a piece of information is positive, negative, or neutral. Tweets on specific topics can be analyzed this way to understand their sentiments.

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Understanding Image Recognition and Its Uses cases

Vision is easy for human brains. We can easily tell apart a tree, a bus, a dog, or an airplane. But its not the same with computers. It takes a lot of effort and skill to teach machines to ‘see’ like us. But humans have been successful in doing so. We have enabled machines with our natural skills to see, learn by example, and understand the world. With the help of computer vision and image recognition, we have taught machines to perform tasks involving vision. And when this capability is brought into businesses with a practical purpose, all this effort is worth it. 

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Learn About State of the Art Sentiment Analysis Algorithms

Introduction to Sentiment Analysis

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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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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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