Machine Learning Online Training
Machine learning is a subset of Artificial Intelligence which creates algorithms on top of which computers learn how to execute the tasks from the data avoiding the programmatic approach of writing code for these tasks.
At this point we know that Machine learning is a part of Artificial Intelligence, as these two words buzzing these days there is a perception that they are same. But, there is a difference, AI is used by machines to implement tasks which we consider as ‘smart’ where as ML is an application of AI where machines are given access to data to learn themselves.
AI has been coined back in 90’s but it has been rapidly came into existence when companies are witnessing huge data generated by the consumers across the industries and it was difficult task for them to process the huge data and take a decision on that data.
After being aware of this scenario engineers thought that it would be feasible for writing code to make machine learn and think like human being and giving access to information present on the web than teaching them everything.
Neural networks are used to teach the computers to think and understand as humans, while holding their natural capabilities like speed, accuracy and unbiased.
The same way human brain classifies the data is the way neural networks are designed so that they can be taught to recognize etc.
Neural networks work on the principles of porbability which makes it possible to draw conclusions, makes decisions or predictions on the data which is fed to it. It has a feedback loop which enables it to learn whether it’s decisions are right or not and plan its approach for future decision making.
Another field of AI – Natural Language Processing (NLP) – has become a source of hugely exciting innovation in recent years, and one which is heavily reliant on ML. It is an approach to understand natural communication either written or spoken of humans and revert using same natural language. To understand the natural language of humans ML is used.
Credit card companies can detect the fraudulent transactions which are outside the normal purchasing behavior of the end user.
Assisting companies in eCommerce industry to keep track of their customers buying patterns like which products are bought together.
Banks can use ML for getting an idea on credit worthiness and chances of default for personal loans etc.
The ability of categorizing information from text such as emails, chats, documents and even tweets helps in spam filtering, information extraction and sentiment analysis.
It identifies the faces or any specified object in an image that users manually tag.
Machine Learning is also involved in driver less cars that makes the car to learn and analyze the traffic signs and drive accordingly.
And there are many applications of ML which can be seen in near future which makes human life easier.