How development in deep learning impacts data scientists

Deep Learning is one of the most important disruptive technology and is one of the vital skills for aspiring data scientists. It is a specific subfield of machine learning that involves learning through successive layers of increasingly meaningful representations. In deep learning, data of layered representations are learned through models called artificial neural networks. Although the structure of such artificial neural networks are inspired from the structure of human brain yet it would be wrong to say that deep learning models are models of the brain!

Is Deep Learning important for your Data science career?

The enormous boom in data creation and storage capacities across the world has really brought Data science to the forefront as innumerous organizations want to leverage data. However, huge data sets have also made the work of data scientists and data analysts very tedious and time consuming. However, Deep Learning is a great skill to have for such data professionals as Deep learning models are very helpful to them.

Machine learning is a concept with several definitions, but at its core, machine learning is a system that can modify its behavior autonomously based on its own experience. The human interference here is minimal. Such a behavioral modification basically consists of establishing logical rules that aim to improve the performance of a task or, depending on the application, to make the most appropriate decision for the context. These rules are generated based on pattern recognition within the analyzed data.

For example, is a person types the word data science into a search engine, the service needs to analyze a series of parameters to decide whether to display results equivalent to data science or analytics, two possible meanings. Among the numerous parameters available is user search history. This is a very simple example, but it illustrates some important aspects of machine learning.

Another aspect is the constant data entry that favors the identification of new standards. Suppose the word "brave" becomes a slang term associated with a cultural movement. With machine learning, the search engine will be able to identify patterns that point to the new meaning of the term and, after some time, will be able to consider it in the search results.

There are several approaches to machine learning. A well-known one is called deep learning, where large amounts of data are treated from several layers of artificial neural networks and algorithms inspired by the structure of brain neurons that solve very complex problems, such as object recognition in images.

How exactly Deep Learning helps data scientists?

A data scientist has to deal with data sets of enormous volumes and according experts in the field, Deep Learning can be utilized to automate everything which requires a human!
The chief job of a data scientist is to extract crucial information out of data sets so that organizations can take decisions based on that. However, the entire process can be painstakingly slow and sometimes even prone to error. Thus, with deep learning models, data analysis can be achieved very fast automatically and therefore helping data scientists immensely!

Will Python skills help you to master Deep Learning?

There is a reason why Python is extremely popular in the field of data science and it is because nothing is as powerful as python be it for coding or for providing an atmosphere for data science operations. The Python package itself comes with innumerous libraries tailor made for crucial data analytics operations such as:

• NumPy and SciPy for advanced mathematical and scientific calculations

• Pandas- a library tailor made for data analysis on Python

• Matplotlib- library for data visualization

Thus, Python is already vital for aspiring data scientists and analysts.

What about Deep learning with Python?

It is not only possible to build Deep learning models on Python but also very advantageous. As a matter of fact, the popular Deep learning framework called Keras is written on Python and in order to use Keras you need to be proficient in Python. Even basic python scripting skills will allow you to know more about Deep learning. Thus, Deep learning with Python is easy and one may go even farther to state that Python is essential to acquire Deep Learning skills!