Should we adopt Machine Learning as a future in Artificial Intelligence?

Machine Learning is basically part of Artificial Intelligence that is comprises of different algorithms called as machine learning algorithms. These can be implemented by using different programming languages like Python (first and foremost for machine learning algorithms implementations), R Programming language, Java, JavaScript, Julia, LISP etc…

 Let’s decide this by keeping in view all of the advantages and disadvantages of ML that whether we should adopt it as a future language in digitization and IT world or not? Let’s begin with the following given pros and cons provided by the specialists of UK in Premium Dissertation UK

Pros and Cons of Machine Learning specified by Premium Dissertation UK experts:  

              Machine Learning is basically the foremost application and branch of AI which is leading in predicting outcomes by focusing mainly on AI applications.

The goals of computer are now trying to make decisions without humans’ interaction which is still in progress but not accurate all the time, ML is also a product of this keen wish of computer. 

          Even google itself says that ML is the future, hence it is clear that machine learning is going to be a tremendous life changing future especially for researchers. But it is often stated that a coin has two faces, each have different pros and cons. The main cons includes :

  •  Huge data needs to be reviewed again and again and there are also specific patterns that are not showing to humans so machine learning is best for doing this work.
  • It do not requires human interaction and you don’t need to work on step by step procedures like other fields of AI and IT.
  • It’s accurate and efficient including flexibility advantage too. It improves it’s algorithms whenever you provide more and more data without caring about the headache of huge data.
  • It also handles variety of big data and multi-dimentional data too.

It delivers best personal experience to it’s  customers wherever it is applied.

Taking aside all of the above benefits of machine learning, we cannot take a side from its negative aspects too. It’s main limiting factors are:

  • As it is stated that it requires big or massive data that must be unbiased and should be good in quality, which is really time consuming and sometimes impossible to get and assemble such data.
  • Machine learning requires time to learn it’s difficult algorithms and to be expertise in them with efficiency and accuracy. 
  • It requires heavy computer systems which is not affordable sometimes.

Machine learning is good but it’s also susceptible to errors like if you want to train an application based on machine learning algorithms and if you don’t have big data then it would be not possible to get desired results because it requires biased training set for it’s outcomes.     

       All of above aside, advancement in AI field has created a way in which positive changes in education system are helping to enjoy their training process. 

        It is said from Premium Dissertation UK writers  that there is not a dumb mind, there is always a trained or an untrained mind, so machine learning is comprised of basically a trained application of biased data.

            Search engines improves their policies and procedures due to machine learning because search engines rely on it. Infact by using it google has labeled so many amazing services just like image search, voice or speech recognition systems etc.

Machine learning is the present tremendous application and has learning techniques that can’t be neglected easily in AI. Time will decide that how it will come up with something new and mind blowing features and improvements.