In the future, data science is predicted to be the default strategy among many HR teams. Many experts commented that the past few years is unarguably the year of data science where deep learning took the biggest part along with AI and machine learning.
Deep learning is an area of automatic leaning in which deep neural networks are studied. It is the type of machine learning that trains a computer to perform human-like tasks. However, different from machine learning that focuses on the bigger picture, deep learning sets up basic about data and trains computer to learn on its own and solve its own problems by recognising patterns using many layers of processing.
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Sas institute explained that deep learning is to replace traditional formulation and specification of the model with hierarchical characteristics, allowing the system to generalise well, adapt well, and continuously improve new data that arrives.
According to Pedro Domingos, deep learning has helped human’s task in terms of vision and speech recognition like self-driving cars and virtual assistance in 2019. This year, deep learning will take up a higher stage such as cognitive ones like language understanding and commonsense reasoning. What does it mean for HR?
When deep learning reaches the level of language understanding and commonsense reasoning, HR can predict better on how to improve human capital performance by data that is stored in the algorithm. For example, after sufficient training, deep learning algorithms can begin to make predictions or interpretations of very complex data. As a result, HR can get the following points:
Maximise your talent-hiring strategy and retention methods. In a fine term, deep learning combined with existing data can solve crucial employees and business problems. Yet, your deep learning usage should be accompanied by some important tools to get the most effective results. Based on Bright Computing data, here is what you need to help your deep learning performs better.
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