The main objective of machine learning is to create a brain like the one that human possesses, almost. It relies on the principle of learning patterns or like gaining knowledge from empirical experiences to come up with similar new results.
The main objective of machine learning is to create a brain like the one that human possesses, almost. It relies on the principle of learning patterns or like gaining knowledge from empirical experiences to come up with similar new results. It involves many research fields like computer science, function approximation, statistics, control theory, optimization, computational theory, decision theory, and experimentation.
In one of the studies it was found that by 2020, almost around 57% of buyers will depend on companies that can predict their buying nature or what they possibly can think of buying next. Call it a prophecy that the consumers are waiting for and here is where AI gets introduced to keep your share of customers. How far has the machine learning technology come?
How far has the machine learning technology come?
When we are talking about the progress of machine learning, researchers have come a long way. A number of different driving platforms have come in fronts such as deep learning, adversarial learning, reinforcement learning, dual learning, distributed learning, transfer learning, and meta-learning. Out of all, deep learning has seen the light of day in many nations. The entire world is focusing on deep learning due to many reasons including the following:
- It is based on multi-layered nonlinear neural networks.
- It has the ability to learn from raw data
- It can extract as well as abstract features from different layers to produce results like regression, ranking or classification.
- It has made some ground-breaking progress in computer vision, natural language and processing and in some way has also surpassed the human level.
- Machine learning was able to do all this because of big data, big computing, and a big model.
Now the question is what will be the future of machine learning, and which of them we must be following? Here are five of the many, that can come up with some groundbreaking innovations in the future of machine learning.
1. The unsupervised improved algorithms
In an interesting method of predictions, unsupervised algorithms are built, which extracts inputs from the data-sets in case only input data is available. Such advancement in machine learning will simply result in better, faster and more accurate predictions.
2. When personalization is enhanced
This algorithm is used to come up with automatic recommendations to users and influence or entice them to come up with certain actions. This smart algorithm synthesizes the information in data and comes up with conclusions, like a user’s interest. It would be able to deduce a user’s browsing activity and will discover that the user seems to be interested in buying certain items. Turning this data into offers will bring success in a massive way.[…]