The Future of Machine Learning in Everyday Life
In the Current era, machine learning using in different fields like health care applications, IoT appliances, Robotics, Machine Vision Applications, Personal assistants(chatbots), financial systems, and the e-commerce industry, etc. Of course, it is not a hypothesis but this will definitely change our life. Here we can discuss the future of machine learning with Ten Interesting fields and these fields improve Everyday Life. Remember this machine learning is a type of artificial intelligence and deep learning is subfield machine learning.
- Auto Health Checkup
- Privacy Protection In Online
- 3d graphics generation
- Credit Risk Management
- Automate Routine/Boring Tasks
- Tasty Recipes Cooking
- Auto Computer Code Generation
- Simulations Models to Tests
- Bulk People Behaviour Analysis
- Identical Security Devices
Auto Health Checkup
AI auto-check your health status in realtime. it can reduce health risks and upcoming serious issues. in simple words, the sensors collect the health data like blood pressure, heart rate, sugar levels, blood oxygen levels, sleep time data, etc., and the collected data analyze with simple machine learning algorithms and will give predicted results. the machine learning algorithms very accurate and proved in different situations.
Privacy Protection In Online
In Everyday Life, we open different websites to different services like shopping, read blogs, social media, emails, and communications, etc. . so these services all running online. we use antivirus software, firewalls, executable plugins to avoid the risk when we in online. but these tools always not protect our privacy. suppose an attacker attack with background scripts, they can access out recent browse history, stored cookies, in-memory local storage files and collect our data easily. so AI protect sometimes in these issues.
3d graphics generation
we can generate 2d, 3d graphics with machine learning, this idea comes with Ian Goodfellow when he submitted GAN paper. I really surprised it can generate fake image data, and fix damaged image files with encoders. we can generate our comic characters also in 3d. so this is a very interesting field. I just tried to use conditional GAN's alongside CNN. it is working awesome.
Credit Risk Management
we can avoid the credit risks with machine learning like fraud detection, over budget flow, budget estimations, customer behavioural analysis etc. It will work pretty sure when we have large size train data. this is a really very interesting field and it can avoid our personal budget overflow too.
Automate Routine/Boring Tasks
we are receiving many messages from different sources. we have enough time to read all the messages. so we just implement an agent here like a robot. it can auto-reply to general messages and categorize messages too. so we can't do that again and again..like another example we need to collect a report at a specific time. it is a routine task, so give this task to agent, it will finish the job.