Most Common & Day-to-Day Experienced Examples of Machine Learning & Deep Learning

Artificial Intelligence is a technique which enables computers to mimic human behavior or to achieve human and super-human abilities in machines that can help us in every-day lives. In other words, it is the area of computer science that emphasizes the creation of intelligent machines that work and reacts like humans. One of the most trending applications of AI is Machine Learning (ML), in which computers, software, and devices are programmed to perform very similar to human brain (cognition). Machine Learning provide computers with the ability to learn without being explicitly programmed and to take intelligent decisions. It also enables computers, software, and devices to grow and improve with time and experiences. So, in general, machine learning is about learning to do better in the future based on what was learnt and experienced in the past.

Here, we are sharing few examples of machine learning that we use almost every-day and perhaps have no idea that they are driven by ML!

1. Face Recognition

Face recognition is one of the few biometric methods that identifies an individual by comparing live capture or digital image data with the stored record for that person. It compares selected facial features of the person’s face from the range of facial database present with the system. It is commonly used for security purposes but are increasingly being used in a variety of other applications.

Few of the applications related to Face Recognition are:

•          FaceLock
•          TrueKey
•          FindFace
•          FaceVault
•          Face Lock Screen

2. Speech Recognition

Speech Recognition also known as "automatic speech recognition" (ASR), "computer speech recognition", or "speech to text" (STT) is mostly used for understanding voice by the Human or computer and performing any required task. In speech recognition, a software application recognizes spoken words. It translates the spoken words into text then decodes it and gives the desired result again in the form of word. These days, we are using it as our virtual personal assistant. Few of the Speech Recognition technologies in current market are:

•          Baidu -  It is known as the "Google of China"
•          Hound - Silicon Valley company SoundHound's flagship product
•          Siri - America's most-used personal assistant “Apple's Siri”
•          Google Now -  Google's voice search for Android phones
•          Microsoft Cortana - The Microsoft phone assistant
•          Alexa – Amazon Speech recognition product

3. Social Media Services

Deep Learning Analytics are playing big part in personalizing our news feed to better ads targeting,  social media platforms are utilizing machine learning and deep learning for their own and user benefits. There are many examples that one must be noticing, using, and loving in their social media accounts, without realizing that these wonderful features are nothing but the applications of ML & DL.

•          Videos recommended for you: Facebook
•          People you may know: Facebook
•          Similar Pins: Pinterest
•          Face Recognition: Facebook while tagging your friends

4. Product Recommendations

Machine Learning and Deep Learning are doing magic these days by refining our shopping suggestions. You shop for a product online once and then you keep receiving emails for similar shopping suggestions. If not this, then you might have noticed that the shopping website or the other add posting apps or the app you use frequently like some games/picture editor/rediffmail etc. recommends you some items that somehow matches with your taste. Based upon your behavior with the website/app, past purchase experiences, items added to cart, Items you are interested in, brand preferences etc., the product recommendations are made.

5. Prediction in Retail

It is not only useful for customers by recommending them products as per their own selection/behavior. But, also very helpful for Retail Industries. Earlier we were able to get insights like sales report from last month/ year/ 5-years/ 10-years/ Festivals etc. These type of reporting is known as historical reporting. But currently as business is growing with the help of Predictive Analytics they are adapting new technologies and are more interested in finding out what will be their sales for next week/ month/ year/ festivals, etc.

So that business can take required decision (related to procurement, stocks, etc.) on time.

But it is not only limited to the above shared examples. But there are several ways where machine learning has been proving its potential and making the technology smarter. Let us know how the technologies in Machine Learning is changing your day-to-day life and share your experience with us in the comments sections below. Suggestions are also most welcomed.