How COVID19 Pandemic Has Been Tackled By Data Science?
This article was published as a part of the Data Science Blogathon
Machine learning and data science have played a vital role in the fight against the recent deadly pandemic known as COVID19. Almost all countries have been using some way or the other this data science, machine learning, and other means of statistical analysis to see the growth rate of the curve of the infected patients and to realize the death rate caused due to this pandemic.
Nevertheless, there are several difficulties in this domain, and it is high time that we address those issues.
The prime struggle in the data science applicability towards covid19 is collecting the data. This appears to be one of the usual challenging obstacles that all data scientists are suffering right now. One aspect of collecting numerical data is to predict the curve of death and affected people.
The other application of machine learning is to apply deep knowledge and advanced machine learning to classify X-Ray images of COVID19 patients and regular pneumonia patients. The CT scan images of COVID19 patients are also available for machine learning and deep learning applications. To make these successful applications, one needs powerful high-end processors that may not be available in this challenging time to all countries’ medical scientists.
Besides, data science and machine learning can help to do the following performances as well.
1. It can help discover the need for this hour; drug discovery technology can be uplifted using machine learning and deep learning.
2. It can help decide the red zone, orange zone, and green zone based on the density of the infected patients.
3. It can do the feature extractions from the images of covid19 patients to understand the virus’s behavior.
4. It can also justify the source from where the virus originated; that will help estimate the next significant outbreak.
Data science and machine learning can significantly help segregate the patients based on the severity of the infection. Doctors can decide whom to keep quarantine and who to provide proper medications or treatments.
Data Science can predict the possible outcome of the treatment.
The geographic segregation based on the locality in terms of country wise, state wise, district wise, and then finally as continent wise are also possible using machine learning and data science. For example, the COVID19 pandemic has been more severe in European countries and the USA than in Asia, Australia. etc. Using the pattern from this data, the experts can normalize it to build a generic statement related to the growth of infection rate, death rate, and a decision made when the COVID patient graph shall be flattening (possibility)?
In this pandemic time, deep learning can also be a valuable tool. It may analyze the facial expression by the facial screening of infected patients(This may be a possibility).
The other significant point is to ignore the outlier from the data sets, such as image and numeric data related to covid19 patients and infection rates. However, it needs a piece of expert knowledge.
Lastly, the data science expert must build their model, keeping in mind that it can not be completely perfect. They have to consider their models with some reservations. The catch is that these models are just helping hands towards the successful treatment of COVID19 infection.
We hope that we will soon achieve success by eliminating coronavirus cases from the earth using multi-dimensional treatments, including data science and machine learning. Let us pray to god together.
Do We Have Enough Data Scientist Jobs Amid COVID-19 Pandemic?
The recent ongoing coronavirus pandemic has engendered many job losses across all industries. The rate of unemployment is growing like never before. Almost 3.8 million people lost their jobs last year in the USA because of COVID19. Moreover, the global economy likely to be gravely affected in the coming times.
In this recession, the data science jobs are bestowing some sort of good news as a hatful of hiring can be observed in analytics companies. Surprisingly, the salary reduction is also a bit ok with the data science sector. According to The Gardian1, many big US-based organizations have declared the pay-cuts for the organization or are intending layoffs.
“Boeing, last year, announced that the coronavirus had delivered “a body blow” to its business and is weighing laying off 16,000 people, a 10% cut to its 161,000 workforces. Hertz, the car rental company, recently laid off about 10,000 employees in North America and is reportedly considering bankruptcy”-The Guardian.
However, data science jobs have found more minor layoff, fewer pay cuts in comparison with other jobs, and the reasons are as below,
- In data science jobs, techies need to know a specific domain with solid fundamentals in statistics, machine learning, data mining, and A.I. It is tough to find such talents. So with unexpected layoffs, companies have to pay a heavy price as finding such new data-scientists would be an arduous task.
- Data analytics would play a pivotal role in analyzing the cost, reducing the expenditure, segmenting the targetted market at this hard pandemic time. So, at this distasteful time when other industries such as service industries have fluffed up by the COVID19 pandemic, data analytics can do justice to the analytics part, at least.
- Most significantly, countries need health analytics like never before to predict the infection rate, death rate, and tentative timing of an end to this deadly pandemic.
- Employees from analytics companies can efficiently work from home without any hustle. However, this could be true for any software company. In fact, work from hope has resulted in bad outcomes for companies like TCS, etc2.
- “TCS Mulls 75% Of Its Workforce To Work From Home By 2025- says M.D. Rajesh Gopinathan”, “A.I. is the new electricity,”- Andrew Ng says. As long as the company has the data to work with, it would survive.
- It is expected that in the coming times of 2021-22, a massive scarcity of data scientists and A.I. professionals could surge as companies need more and more automation in collaboration with IoT, machine learning, and deep understanding. So, hiring data science experts will increase in 2021-22.
Hence, the above points ground why the ceases or layoffs are less for data science and AI Jobs even during the COVID19 pandemic.
The author’s point of view is the author’s personal opinion, personal beliefs, personal perspective, and personal perspective.
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Mrinal Walia is a professional Python Developer with a Bachelors’s degree in computer science specializing in Machine Learning, Artificial Intelligence, and Computer Vision. In addition to this, Mrinal is an interactive blogger, author, and geek with over four years of experience in his work. With a background working through most areas of computer science, Mrinal currently works as a Testing and Automation Engineer at Versa Networks, India. My aim to reach my creative goals one step at a time, and I believe in doing everything with a smile.
Thanks for Browsing my Article. Kindly comment and don’t forget to share this blog as it will motivate me to deliver more quality blogs on ML & DL-related topics. Thank you so much for your help, cooperation, and support!
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