Machine Learning Vs Deep Learning

Machine Learning Vs Deep Learning – Complete Comparison

Artificial Intelligence (AI) is moving this world, which was never than expected. Today, the IT-enabled, internet-enabled services and robotics perform as the human mind thinks. These were happening due to machine learning (ML). In the later stages, deep learning (DL) evolved as many types of researches were going on in AI. In the earlier period, ML and DL were subjects of AI. Today, a deeper focus is on DL, which makes them as a separate subject to study and research. Here, we have discussed the ML vs. DL in simple language.        

What is Machine Learning

What is Machine Learning

When it comes to data analytics and finds a solution from them, Machine Learning is a method to input data in computer and interpret in such a way that it needs lesser human intervention. Her, it thinks like a human with the given data or algorithms. Here, computing professionals use the general-purpose programming language.  ML is one of the subjects in Artificial Intelligence. ML is used in various businesses and services to ease human errors and serve better.

What is Deep Learning

What is Deep Learning

Deep learning is the trending subject in AI. It is a wider concept of ML. It uses the deep neural network as the human brain does. Here, the output is better than ML by using layered data. It has many capabilities than ML to bring accurate output without any human interpretations. Here, it uses big data to compute. The use of DL in Cloud and Big Data computing has taken the corporate companies to the next level or the state of art AI to use in their business.   

Machine Learning Vs Deep Learning

  • ML is a traditional Machine Learning. DL is an advanced one in Machine Learning, which recently evolved as a new subject in Artificial Intelligence. 
  • In ML, algorithms are created in such a way that the machine will do the rest without any human intervention. On the other hand, the DL relies on artificial neural networks (AAN). It is similar to human neural networks, which function in the human brain. 
  • ML uses limited algorithms to do some specific tasks without human intervention. Dl needs huge data as it uses AAN.
  • ML can solve simple queries without human interventions. DL can solve complex queries without human interventions.
  • ML capabilities are less when compared to DL capabilities.
  • ML is limited to standard machine learning models. DL uses AAN and decides how the human brain thinks.
  • ML depends on feed algorithms. DL acts like a human-like AI. 
  • ML has limited opportunities to serve this corporate world. On the other hand, DL and Big Data Computing can take the corporate world to the next level by simplifying their works through Artificial Intelligence or AI-enabled services. 
  • ML is the best to use with given limited data. DL needs big data to perform from the layered structures of data. Here, ML will outperform DL on doing specific tasks without human intervention.
  • ML needs very limited IT-infrastructures to perform companies and other services. On the other hand, DL needs large scale IT-infrastructures. 
  • ML breaks the problems at different levels to find a solution. DL is the best to apply to find end-to-end solutions. 
  • ML takes very little time to train from Starch. Whereas, DL takes a longer time to train from Starch.  
  • As of today, ML has limited opportunities for research works. On the other hand, DL has vast opportunities for research works. This is due to data science.
  • ML has limited Interpretability. DL can do better Interpretability with difficult to impossible levels, where ML cannot do so. 
  • ML has limited accuracy on the output it gives. Dl has higher accuracy on the output it gives.
  • ML has limited access to Cloud Computing. On the other hand, DL has vast opportunities in Cloud Computing.
  • ML has a limited future with the small-scale business. DL has a vast future with large-scale companies all over this globe. 
  • ML has a limited scope in digital marketing. DL has a wider scope in digital marketing. 
  • ML partially supports Big Data Computing. DL deeply supports Big Data Computing.
  • ML has limited scope for expansion in its models. DL has many scopes for expanding its model.

Hence, deep learning is the trend and the future of Artificial Intelligence. This does not mean machine learning ML is of no use. Both of them are needed to ease our lives with the latest gadgets, internet of things, Smartphone applications and many more on the list. Hence, we are benefited directly or indirectly in your daily life with the use of ML and DL by making use of Artificial Intelligence technology.

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