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Most parents feel some fear when allowing their young children to navigate the internet unaccompanied. Many games, such as Minecraft, have a chat feature. Most people on the other side of the screen are children of a similar age, however, there is no way to ensure this. In these chatrooms, kids could be chatting with an adult. Unfortunately for children and parents, adults are known to have slightly more colorful vocabularies than children.
Most of these applications and games are entirely unmonitored, and parents expose their children to any type of person when they allow them to communicate online. The type of content that children are exposed to when dealing with strangers could be explicit. And even though some games, such as club penguin, have automatic filters, more popular games do not.
One of the biggest fears for parents is unsafe language in chatrooms, especially for young children. This may be a barrier to engagement for businesses catered toward young people. However, using machine learning, a business can train a system to filter out particular words and their suffixes.Read More
The early detection of diseases is crucial in the process of improving a patient’s health. However, this task can be time-consuming and complex, especially since many serious ailments can present themselves as the common cold or the flu in their early stages. The high demand for specialists that are able to discern illnesses causes many issues in early detection of diseases because they are often focused on more high profile cases. By using an ML system for predictions, we can drastically improve a patient’s chances of survival, in both pneumonia detection and other cases where radiology is necessary for early detection.
Computer vision technology is one of the many solutions to the issue of early diagnosis for serious diseases that may not present themselves as serious. A specific type of computer vision technology, called image classification technology, is the process that Skyl, a machine learning platform, used to automatically label whether or not an X-Ray image of a lung is one with pneumonia. Skyl has used it’s platform to create this project. It uses a deep learning methods, ensuring each prediction becomes more accurate as it receives more data. However, image classification technology is not limited to a single class, there could be multiple different categories that an image falls under. For example, a picture could contain a dog, cat, or fish. In this particular case, there were only two categories, pneumonia and not pneumonia.
The Skyl Solution
Using Skyl, healthcare professionals can input data various from sources that have labeled data. For the lung project, Skyl used pre-labeled data from the National Institutes of Health Clinical Center. Using only this data and our platform, Skyl successfully created a project and we were able to train the algorithm, and deploy it on our website. However, this is only one example of how Skyl’s platform can be used. Image classification technology in the healthcare industry has been used to diagnose different forms of cancer, check for fractures in X-Rays, and process MRI scans. By automatically moving certain cases to a higher priority, doctors, nurses, and radiologists waste less time ignoring patients who may have serious ailments.
The uses of image classification technology are not limited to the healthcare industry and radiology. The same software that classifies images can classify any type of unstructured data which includes audio, video, and images. This technology has been used to analyze satellite images and deforestation, find explicit words in music, and detect faces. We have only dipped our toes in the future of image classification technology and how it will affect the future of the way businesses, schools, hospitals, and our day-to-day lives are conducted. Certain companies, such as Skyl, are dedicated to making sure that every company on the planet can create a machine learning project, because we do not have all the ideas, other people do! We just hope to get enterprises to a point that their ML dreams can become a reality and not just a fun idea in the office.
Skyl.ai is a SaaS platform that allows any business to streamline a computer vision or natural language processing project. Visit Skyl.ai to learn more about the future of computer vision technology and how it can impact your business!
Since it’s invention, the internet has changed the way we shop, stay entertained, and communicate. eCommerce sites have rendered the Sears catalog obsolete, watching movies is no longer limited to going to the theater, and the structure of a 9–5 is shifting as more employers allow their employees to work from home. The internet has provided a myriad of conveniences and options for shopping, entertainment, and employment. However, unlimited options being readily available has resulted in problems that hurt both businesses and their customers. A single website that sells one specific product such as perfume can have hundreds of options, and there are so many websites for perfume. Contradictory to common sense, a larger number of choices is better for the consumer because they are more likely to find what they want. However, when faced with too many choices, this decision can become complex. Consumers face thousands of choices at their fingertips which is often overwhelming.Read More
Natural language processing (NLP) is the process through which computers read, understand, interpret, and respond to human language. Any business that has a need to read and interpret text can implement NLP. For example, companies can automate analyzing consumer reactions to a new product or service using sentiment analysis.Read More
The Skyl team gathered with data scientists and CEO’s this week to chat about the future of AI in the digital media and marketing landscapes. We learned more about the potential use cases for machine learning in these industries, as well as issues that teams run into while creating data science projects.
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Some of the issues that these marketing and media leaders talked about were:
- The inability for data science teams to properly communicate how timely and costly certain projects are to their managers
- It is difficult to gather data properly
- Buying labeled data, creating a project, and finding out that the data is not serviceable
- Properly integrating unstructured machine learning projects without a high initial investment
We guided them through Skyl.ai, and let them lead a discussion on how our platform could change the way that their business is conducted.
These use cases for Skyl.ai included:
- Sentiment analysis for public tweets
- Image processing to personalize the targeted marketing advertisements
- Natural language processing to learn new slang and find sentiments faster than their employees
Skyl.ai is a platform created for making the end-to-end machine learning workflow accessible for any person from business students to data scientists. Visit Skyl.ai to learn more about our platform and projects!