Machine learning and artificial intelligence are two terms which have been used most frequently in data industry and well, there is a reason for this.
None of the technologies have impacted the modern ways and life of human like these technologies have.
Before explaining the details about how machine learning works, I would like to explain what exactly this is? and how this technology is changing the lives and solving problems.
Machine Learning is the powerful type of artificial intelligence and a widely used method which analyse the data through implicit techniques and computations, thereby making human job less easier and error free.
More specifically, we can say this is a branch of Computer Science that learn from the past and applies the experience to built model for future.
It is widely used to find insights by pattern recognition.
Why its becoming so popular and gaining attention?
Although this has a never-ending answer but major key points are –
1. Error Free
As this type of technology applies implicit algorithms programmed within and tested a no.of times before implementation, so eventually resulting in error-free mechanism.
Comparatively, models made by explicit programming at each level becomes more error-prone.
2.Less time Consumption
The second most useful feature of machine learning. Making a model via machine learning and generalising it for entire report/study helps in
less time consumption and variables can be adjusted anytime for any modification.
Machine learning posses the unmatchable power of making thousand of excellent models in a week or so, while human can maximum make 2-3 good models
within the same time period.
How it is different from data mining?
However, Data mining also uses a lot of algorithms which are by nature, same as used in machine learning.
But the whole approach to choose one between these two is different.
Where Data mining is used to mine the historical records/data, Machine learning has one step added to this, which uses the history to tell future.
There is one parameter on which the accuracy/reliability of model depends-
1). Algorithms– The more better algorithm yields more better prediction.
Some of the famous algorithms are-
Neural Networks, Random Forests, Decision Trees, Bayesian Networks, k-means clustering etc.
Machine Learning is very successfully tried and tested and so, serving almost every area of diverse industries like-
2). Web Industry (search results, SEO etc. )
3). Fixing Price of products (in e-commerce)
4). Image Analysis and recognition (google images etc.)
5). Default Customers Analytics (BFSI)
6). Education Sector
7). Healthcare Industry
8). Animation Industry
and every domain/Industry that deals with different nature of data like text, graphics,signs etc.
Techniques to Learn:
1). Supervised learning- https://en.wikipedia.org/wiki/Supervised_learning
2). Unsupervised learning- https://en.wikipedia.org/wiki/Unsupervised_learning
3). Semi-supervised learning- https://en.wikipedia.org/wiki/Semi-supervised_learning
4). Reinforcement learning- https://en.wikipedia.org/wiki/Reinforcement_learning
At this stage, we all understand how effectively machine learning can be used for powerful insights and research, we should not forget the data collection & visualisation techniques (via different tools depends upon one’s hands-on) so that we can make better use of ML.