Machine Learning and Artificial Intelligence
Machine Learning and Artificial Intelligence are creating a huge buzz worldwide. The plethora of applications in Artificial Intelligence have changed the face of technology. These terms Machine Learning and Artificial Intelligence are often used interchangeably. However, there is a stark difference between the two that is still unknown to the industry professionals.
Let’s start by taking an example of Virtual Personal Assistants which have been familiar to most of us from quite some time now.
Working of Virtual Personal Assistants –
Siri(part of Apple Inc.’s iOS, watchOS, macOS, and tvOS operating systems), Google Now (a feature of Google Search offering predictive cards with information and daily updates in the Google app for Android and iOS.), Cortana (Cortana is a virtual assistant created by Microsoft for Windows 10) are intelligent digital personal assistants on the platforms like iOS, Android and Windows respectively. To put it plainly, they help to find relevant information when requested using voice. For instance, for answering queries like ‘What’s the temperature today?’ or ‘What is the way to the nearest supermarket’ etc. and the assistant will react by searching information, transferring that information from the phone or sending commands to various other applications.
AI is critical in these applications, as they gather data on the user’s request and utilize that data to perceive speech in a better manner and serve the user with answers that are customized to his inclination. Microsoft says that Cortana “consistently finds out about its user” and that it will in the end build up the capacity to anticipate users’ needs and cater to them. Virtual assistants process a tremendous measure of information from an assortment of sources to find out about users and be more compelling in helping them arrange and track their data. Machine learning is a vital part of these personal assistants as they gather and refine the data based on user’s past participation with them. Thereon, this arrangement of information is used to render results that are custom-made to user’s inclinations.
Roughly speaking, Artificial Intelligence (AI) is when a computer algorithm does intelligent work. On the other hand, Machine Learning is a part of AI that learns from the data that also involves the information gathered from the previous experiences and allows the computer program to change its behavior accordingly. Artificial Intelligence is the superset of Machine Learning i.e. all the Machine Learning is Artificial Intelligence but not all the AI is Machine Learning.
|ARTIFICIAL INTELLIGENCE||MACHINE LEARNING|
|AI manages more comprehensive issues of automating a system. This computerization should be possible by utilizing any field such as image processing, cognitive science, neural systems, machine learning etc.||Machine Learning (ML) manages influencing user’s machine to gain from the external environment. This external environment can be sensors, electronic segments, external storage gadgets and numerous other devices.|
|AI manages the making of machines, frameworks and different gadgets savvy by enabling them to think and do errands as all people generally do.||What ML does, depends on the user input or a query requested by the client, the framework checks whether it is available in the knowledge base or not. If it is available, it will restore the outcome to the user related with that query, however if it isn’t stored initially, the machine will take in the user input and will enhance its knowledge base, to give a better value to the end user|
Future Scope –
- Artificial Intelligence is here to stay and is going nowhere. It digs out the facts from algorithms for a meaningful execution of various decisions and goals predetermined by a firm.
- Artificial Intelligence and Machine Learning are likely to replace the current mode of technology that we see these days, for example, traditional programming packages like ERP and CRM are certainly losing their charm.
- Firms like Facebook, Google are investing a hefty amount in AI to get the desired outcome at a relatively lower computational time.
- Artificial Intelligence is something that is going to redefine the world of software and IT in the near future.
Python Example for Beginners
Two Machine Learning Fields
There are two sides to machine learning:
- Practical Machine Learning:This is about querying databases, cleaning data, writing scripts to transform data and gluing algorithm and libraries together and writing custom code to squeeze reliable answers from data to satisfy difficult and ill defined questions. It’s the mess of reality.
- Theoretical Machine Learning: This is about math and abstraction and idealized scenarios and limits and beauty and informing what is possible. It is a whole lot neater and cleaner and removed from the mess of reality.
Data Science Resources: Data Science Recipes and Applied Machine Learning Recipes
Introduction to Applied Machine Learning & Data Science for Beginners, Business Analysts, Students, Researchers and Freelancers with Python & R Codes @ Western Australian Center for Applied Machine Learning & Data Science (WACAMLDS) !!!
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