Top 5 Data Science Applications That Changed the Industry
While Artificial Intelligence has made a significant impact on the modern IT industry in the last decade or so, Data science has also taken over the mantle in recent years in revolutionary development.
Today, businesses are surrounded by fast-paced environments and dynamic ideas that have taken to make the world so much more advanced than it is. On a definitive front, it certainly requires, or rather demands, the increase in the use of modern technologies across industries.
Most companies do not even have to consider thinking because of the unceasing importance tech carries in today’s world. While there is no shortage in the use of AI or data science in the industry today, this blog covers the leading applications integrated with these technologies and the impact they have had.
E-mail Spam Filtering
Are you aware of the spam folder in your email dashboard which you seldom open? It was one of the most dynamic features that changed the way emails are sent these days. The need for an application arose when the number of unwanted emails started surging constantly.
On the back of data science early on integrated with AI and ML, a robust spam mail detection filter was created. Once the testing with it was successful, it was launched as an E-mail Spam Filtering app which is now a part of almost every email platform.
Another notable way of filtering spam messages was to use different algorithms to classify if the email received is spam or not. Other techniques like OCR and neural networking can also be implemented for advanced spam detection. These techniques are used by major companies like Gmail.
Autocomplete is also a feature created with modern technologies. Here, an application predicts the word a user is typing by deciphering the first few letters he or she has entered. This is a very popular feature in smartphones these days and is also better known as predictive text.
In various UIs, users can simply press a tab key to accept a suggestion or the down arrow key to accept one of many suggestions. The Autocomplete application can implement zero-shot and one-shot learning methods that exist for natural language processing.
These same methods can also be used to carry out better training models that improve the overall performance of the app and also help avoid repeated training procedures. This can turn out to be a big hindrance in real-life applications and scenarios.
The Autocomplete feature is integrated into all social media messaging apps, smartphones, Windows applications, and all the popular Apple applications too.
This is another popular typing feature a large portion of the millennial audience is familiar with. Autocorrect is an automated data validation feature that is popularly found in text editing and word processing applications.
Autocorrect is based on AI methodologies that can be very much beneficial to get the desired result even while texting or typing to avoid incorrect words. In this feature, the spellings of a word that a user is typing are automatically checked and the best possible suggestion appears to avoid the wrong words.
There are certain drawbacks with this feature too. One of them is that the AI must be constantly trained and updated. Words can be added or removed from the dictionary by the developers at any point which would lead to certain errors occurring in the actual application.
Again, this application feature is popularly seen in smartphones, Windows applications, and Microsoft applications.
Smart Face Lock
The smart face lock is one of those applications that has gotten popular in recent times. It is a regular feature on almost every mobile device and is extensively used for unlocking the device.
This app was created with procedural human face recognition gaining prominence along with an authorized user name. Face detection is largely considered a simpler and just a beginner-level project. However, it is a crucial step required to build the smart lock face app.
This application was built with histograms derived from various Machine Learning models coupled with Data science. It has provided great convenience to users and saves time in the world too where certain systems can be unlocked at a brisk pace to save time.
A virtual assistant is an application that basically deciphers natural language received through voice commands to complete certain tasks for the user. These applications are powered by AI technologies and have gained more popularity than any other AI app.
Some of the popular virtual assistants going around are Google AI, Alexa, Siri, Cortana, and more. These applications have been a handful to millennial gadget users. While they are very much extensively used on mobile devices, they are also used for more advanced purposes like smart homes, smart offices, and more.
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