Future of Deep Learning in Data Science

Future of Deep Learning in Data Science Francois Chollet is a renowned name in the world of Machine Learning,

and Artificial Intelligence. He is the developer of Keras (a Deep-learning library), Tensorflow (a Machine Learning framework), articles, multiple types of research for machine reasoning, and many more. His contribution to the field is unmatched. In the present times, he is working on building the tools to enhance the working of Machine Learning professionals in every sector, and industry. Keeping all these things in mind, Francois explained the scope of deep learning, machine learning, Data Science education, and artificial intelligence in the future. For this very purpose, he used his keynote address at the ML Summit to influence the next generation of Data Science professionals, and Machine Learning engineers.

The Current Professionals

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At present, the influence of Machine Learning can be found everywhere.

It's omnipresent, and there is no sector staying untouched from it. Even if we consider the health sector, Medical imaging is done with the help of Machine Learning. The Agriculture sector too uses Machine Learning.

Just like web development, machine learning will soon make its way into the toolbox of the developers.

However, to date, machine learning has not been used to its full potential but is expected to grow fully in the next few years.

Future of Deep Learning The future of deep learning can be predicted by its evolution in different fields. The given below trends are considered to witness a rise in the machine learning field.

1. The Scenario of Pre-trained Models The current market scenario of deep learning models in clothes is that if you are creating a new one each time you want it, you will have to start from scratch to get what you want. This has rendered most of the workflow of the most Deep Learning functions as inefficient. This is a big drawback for deep learning engineers in comparison to traditional software engineers.

In the future what we are going to first see is the pre-trained models for every word which can be reused. You would not have to build up a new model for every work, you can simply import what you want, and start working over it.

The present era witnesses a higher amount of human work. Most of the engineers and the researchers are still involved in the various types of manual work, which ideally are the jobs of machines, and algorithms.

In the next few years, it is estimated that we will migrate out from the conventional handcrafted techniques of learning, configurational setups, and many more. Also, Machine Learning, as well as the Deep Learning methods, will become more machine-oriented, less handcrafted, and highly automated. This will benefit Data Scientists tremendously, as they will now be able to focus more on Data Curation and Problem Specification rather than focusing on conventional configuration. This is going to be huge for Data Science, which focuses on the rising scope, and subsequently increased payroll. The person is going to take home a good payout after choosing Data Science as a career option.

3.

Mobile Research Labs

In the current scenario, the research labs are concentrated in a concise place, due to the lesser use of Deep Learning in various fields.

However, due to the growth of Deep Learning in every sector, Deep Learning Technology is going out of the primitive world, to a new world where the Machine Learning model can be taken anywhere where it can be put to use. So, the era of Deep Learning, and Data Science will spike up in the future.

Even today Data Scientists and machine learning professionals are paid huge. This complies with the fact that the demand is more and the supply is less. Almost every field requires a Data Scientist or a machine learning professional to run crucial operations of the company. The important decision-making process also requires a Data Scientist to move further. It is estimated that by the end of 2021, the demand for Data Scientists is only going to rise further making them one of the highly paid professionals.

Top Data Science Certification courses Improving Data Science capabilities is of absolute importance in the days to come. Many researchers have put out the fact that the organizations are searching for data science talent and due to the scarcity of the talent, many job positions are left vacant for the period.

If you are also looking forward to opting for Data Science as a professional career option, you ought to consider enrolling yourself in the fine Data Science Certification course. The path or the certification application will assist you to accumulate all the principal competencies that a Data Scientist job requires. You can even pursue a diploma in the Data Science area from a variety of universities. Below are some renowned institutes

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SAS Data Science Certification Microsoft Certified Azure Data Scientist Certificate course United States Data Science Institute- The United States Data Science Institute (USDSI™) provides technical certifications for aspiring Data Science professionals. There are various certification courses available, both for fresher candidates as well as experienced Data Scientists. The institute has benefited thousands of students to grab themselves amazing job opportunities with money-making jobs.

Cloudera Certified Google Data Analytics Professional Certificate Professional Data Scientist Certificate course

So, these were some institutes offering certification courses at very budget-friendly fee structures. Undoubtedly, choosing Data science as the career option is only going to outdo in the future with the demand rising every moment and every year. The Data Science career option has allowed several aspiring candidates to seize their dream jobs at the most eminent positions in well-reputed companies.