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Watching Machine Learning Change: For The Last 10 Years

What is Machine learning? 

Now some of you may be pondering upon the fact as to what is Machine learning. Well, it’s basically related to the process of handling a large amount of data. Usually, in the business world, there’s always one or the other thing going on. So to handle large processes or facilitate the process, we take help of certain equipment or machinery. This is what makes up the cumulative term of ” Machine Learning”. It includes things like automatic extraction of data or analyzing large data.  Basically, machine learning employs the usage of Artificial intelligence to improve itself over a period of time. Machine learning focuses on the development of computer programs.

For the past 10 years, Machine learning has changed quite a lot. Artificial intelligence has transformed to become more sustainable and efficient. Thus, with time come needs. And the need is obviously the mother of all innovations! 

Take a look at this trajectory of Machine learning


Some machine learning methods

  • Supervised machine learning algorithms apply past learning to new data using examples to predict future events. The system is able to provide targets for any new input after training. The algorithm can also compare its output with the correct, output to find errors.
  •  Unsupervised machine learning algorithms are used when the information used to train is neither classified nor referred. The system doesn’t figure out the right output, but it explores the data.
  • Semi-supervised machine learning algorithms are in between the supervised and unsupervised learning since they use both labelled and unlabeled data for training. The systems that use this method are able to considerably improve learning accuracy. 
  • Reinforcement machine learning algorithms is a learning method that interacts with its environment by producing actions and discovers errors or rewards. 


The ancients of machine learning.

  • The terms “machine learning” first appeared in 1952. It was in 2010 that  George Dahl and Abdel-rahman Mohamed proved that deep learning speech recognition tools are effective. They also mentioned that they can provide some good industrial advantages. This provided an impetus to the process.
  •  At the same point of time, Google dived in the process too. It announced its self-driving automobile project, called Waymo
  • Finally, DeepMind was established in September 2010. It is a pioneer in the fields of AI and deep learning


From 2011 onwards

  • In 2011, Artificial intelligence went on a different path. It literally shook the world. The reason was of it was: 

 IBM’ s question and answer system defeated Jeopardy. 

  • While IBM machines were working on portraying human intellects and other features, Apple introduced Siri, its virtual assistant. Though it was banned by IBM.
  •  Siri uses speech recognition, a natural language user interface, and convolutional neural networks. The technology enables users to conduct searches and make recommendations. It also answers questions, and perform tasks via internet services.


Some other ventures in this field


  •  Besides this, another application -The Oculus Rift is used in many applications beyond VR gaming, including industrial visualization and design, education, and media.  


  • In 2013, Boston Dynamics created Atlas. Atlas is basically a dog-like robot. It is capable to carry out a variety of human activities. 


  • In 2013, Google also introduced a beta test version of Google Glass.  For those who don’t know, Google Glass is a heads-up display mounted on eyeglasses. It supports functions including facial recognition and text translation, besides other functions.  


  • Google turned heads again in 2014. Guess why? Well, it did something completely different this time. It bought another program DeepMind for  $500 million.


  • Also, who doesn’t know Alexa? Well, some people have found a best friend in her! Amazon’s Alexa is again a new process of Machine learning. It is also a milestone set in the department of Artificial intelligence. Who doesn’t want Alexa? 


Just a few years ago 

  • Finally, let’s come to recent times. Around 4 years ago, that is, in 2016,  Google Assistant came up.  We all know what Google assistant is. Don’t we? It is an  AI-powered virtual assistant that engages in a two-way conversation. Thanks to Google’s language!  Google Assistant can conduct Internet searches, schedule events, set alarms, etc.

 It truly plays the role of a reliable assistant.

  • In 2018, a different thing happened. A Paris-based art collective of artists and AI researchers created some artwork. They did it using an algorithm that analyzed image data from some portraits. 


  • Finally, we have landed in 2020. And what we see today is the expansion of Artificial intelligence in all spheres. This not only includes business but healthcare too. If today a pandemic has engulfed us all over, then data scientists are also working to dive into unexplored areas of Machine learning to improve analysis methods.