The latest news on AI

Skyl.ai Featured as a Leading No-Code AI Platform by CB Insights


Over the past two years, the Skyl.ai team has been working diligently to empower companies with the power of AI. In light of the uncertainty posed by COVID-19 in the business environment, it has become ever critical to embrace AI to remain competitive. We at Skyl.ai remain steadfast in our journey to make AI accessible to everyone in these uncertain times and continue to be recognized for our work in AI automation.

We are thrilled to announce that Skyl.ai has been named one of the leading No-Code AI platforms by CB Insights! CB Insights report “Enterprise AI Trends to watch in 2021” provides comprehensive data and expert insights on companies that are pioneering No-Code AI tools to solve real-world problems. We are honored to be included in this prestigious list of the world’s leading AI companies.

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Using Object Detection in Real Estate for Home Price Estimation

Judging the price of a property accurately is one of the most crucial factors in real estate businesses. Buyers access several aspects before purchasing a property. The characteristics that influence a home sale price will generally include the square footage area, location, number of rooms, and the interiors of the house. Other factors that influence the appeal are streets around the house, safety of the area, and its access to commercial businesses, schools, and hospitals. 

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Automatic License Plate Recognition Using Computer Vision

License plate recognition technology has made great progress due to its development and application in intelligent transportation systems. License plate recognition (LPR) is an effective process of recognizing characters on number plates. An LPR system for vehicles can be used anywhere as an automatic surveillance system for identification of vehicles in real-time.

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Detecting Personal Protective Equipment (PPE) Using Machine Learning

There are skyscrapers and architectural marvels all around us. Along with an ever-evolving development in healthcare and major advances in engineering. But we live our daily lives clueless about what it takes to reach this level of progress. With 7.6 million employees and $1.3 trillion in annual expenditure, construction is considered to be one of the largest sectors in the U.S. But it is also the most hazardous industry with a high number of workplace accidents and injuries.

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Machine Learning in Banking – An Overview of Benefits and Possible Use Cases

Machine learning application is growing thanks rapidly to its ability to help businesses automate processes and enhance operations. As the internet proliferates and the need for a growing online presence becomes necessary, companies in various industries increasingly depend on algorithms to decipher complex problems with good assurances toward a solution. Statistics indicate that the machine learning market will grow to $117.19 billion by the end of 2027.

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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 8 Natural Language Processing Techniques

Artificial intelligence (AI) encompasses multiple types of machine learning approaches, including computer vision, natural language processing (NLP), audio intelligence, and so on. As the name suggests, NLP is the branch of AI that centers on language and teaching computers how to understand and use it in a natural, human-like manner.

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