For quite some time, the term “machine learning” and “deep learning” seeped its way to the business language, especially when it is related to Artificial Intelligence (AI), analytics and Big Data. Frankly, the approach directed to AI which provides a great promise with regard to creating self-teaching and autonomous systems that can revolutionize various industries.
What is Machine Learning (ML)?
One of the subfield of AL is machine learning. Here the basic principle is that machine, collect data and they learn it for themselves. No doubt, this is the most awesome tool of the business’s Artificial Intelligence kit. One of the interesting advantages of the ML is that you can easily apply the training and knowledge received from analyzing huge data set to perform various functions and excelling at them like speech recognition, facial recognition, translation, object recognition, and various other tasks.
Compared to the hand-coding a given software tool filled with specific instructions which can be used for completing the task, the ML provides a suitable system to understand the pattern by itself and make the required predictions.
What is Deep Learning?
Frankly, a subset of the ML is called as deep learning. Here one utilizes ML techniques for solving various real-life issues, and this is possible by accessing the neural networks which easily help in stimulating the decision-making of human beings. In addition, deep learning is kind of expensive and one will need extensive data sets to train. This is because there are various number of parameters that one might need to have an understanding, possible by learning about the algorithm. Thus, this can be present at the initial stages and create various kinds of false-positives.
To have a fair understanding, let’s check how deep learning algorithm can be used for understanding how a cat looks. So, a huge amount of data set of pictures is used for underlying the basic details which separates the cat from other like panther, cheetah, fox etc.
How Machine Learning And Deep Learning Affects Job
There is a kind of hysteria of doom-and gloom surrounding the machine learning AI. The majority of it is all about how people will be out of work, as there are quite successful stories where machines were able to carry out specific job-related works and bought about extensive results in it.
Indeed it has become a huge paranoia, but it turns out that machine learning only performs tasks, and not the job. Of course, many tasks constitute a job but ML programs are not much flexible.
However, it doesn’t mean that both machine learning and deep learning will not affect your job, as they have already done and will simply continue to do so. Most importantly, whether it will be a benefit or threat will depend on how you are going to react when you identify it.
No doubt, there are quite a lot of reasons on how white-collar jobs can be a great invitation for deep learning and other related technologies. There are various experts who feel that the professional impact which AI and deep learning along with other automated technologies can drastically affect the work force count.
In short, there have been certain reactions or changes with regard to how machine learning and deep learning brings. It has drastically reduced the role of various professionals who are considered as knowledge gatekeepers. Plus, there has been a positive trend towards proactive and reactive services.