The prime objective of this article is to examine the various aspects of machine learning. The article goes on to examine the importance of machine learning in the current times by highlighting well researched facts. Thereafter, the post looks at the feasibility of choosing online machine learning courses to enhance the understanding of machine language. The write up concludes with suggestions about the right choice.
Machine learning is defined as the process by which machines learn to take decisions without the aid of humans. As such machine learning may be supervised, unsupervised or semi supervised.
According to McKinsey, “Machine learning is based on algorithms that can learn from data without relying on rules-based programming.”
Establishing importance of machine learning
The importance of machine learning is itself established from the fact that if is part of artificial intelligence without which the next generation technology would stop to evolve. Here is a list of facts which not only highlight the importance of machine learning but also clear beyond doubt that it is the most pivotal parameter in training machines.
20% of C-Suite makes use of process of machine learning.
- 850+ – The total number of anecdotes penned down by various newspaper journals over a period of last few years, if we take a round off figure.
- Machine computing and soft computing modes can be deemed as the most frequently googled tools on web platforms.
- About 9000 is the number of persons who own the necessary acumen and the desired skills to solve pressing AI problems.
- 95% – The efficiency that can be related with soft computing techniques which have been used to save a patient’s life.
- 63% – The probability of soft computing in estimating the boom and bust cycles in the market.
- 75% of various geriatric and mental disorders treatment services in different countries may be handled by advanced technology and humanoids.
- 5% The probabilistic analysis of the malfunctioning of measurement related instruments.
- 39% of the total worth created by data modelling techniques which are used by devices related to deep neural computing.
- 90% – The assumed level of efficiency of various algorithms in determining the prevalence of a cancerous cell.
- Deep learning and the techniques of neural computing which are imbibed by humanoids are good at oratory skills than humans.
The right methodology for understanding machine learning
There is not one methodology to choose from. In fact, there are numerous ways to master the art of machine learning. However, we restrict our focus in this context to the choice between online and offline machine learning courses.
If you are thinking of getting equipped with machine learning via a classroom module, then this may not be a bad option for its own advantages. There are numerous training institutions which provide machine learning course in gurgaon. The best thing about these institutions is that they are equipped with state of the art facilities and programs. The faculty is also specialized in machine learning architecture. So they have the capacity to provide a deep and thorough training to their students.
Major benefits of choosing online machine learning course:
1- Accessible remotely from anywhere without the restrictions like time and travel.
2- Relatively cheap as compared to offline courses.
3- Provision to watch a module multiple number of times.
4- Doubt clearing sessions can be arranged separately.
5- The resource set provide in an online training course is usually wider than one in the offline module.
The choice between online and offline machine learning course can be resolved by selecting from a personalized genre of various factors. The factors may range from flexibility to cost and timings. Largely, the online module is deemed as a favourite over the offline module.
Whether the machine learning course is online or offline, the best thing is that at the end of the course, you are a trained professional of machine learning with a skill set large enough to guide and control the behaviour of a machine.