In the last few years, big data has become central to the tech landscape. You can consider big data as a collection of massive and complex datasets that are difficult to store and process utilizing traditional database management tools and traditional data processing applications. The key challenges include capturing, storing, managing, analyzing, and visualization of that data.
In recent years, machine learning has been one of the most talked about tech topics and is being applied to businesses widely. Put simply, this application of artificial intelligence allows computers to learn and improve without being programmed directly. The revolutionary technology presently forms a highly crucial aspect of countless established, as well as, burgeoning industries. Let’s have a look at the key reasons why you should start preparing now to become a machine learning professional.
A significant number of newcomers in data science tend to spend a huge amount of time to develop theoretical knowledge and earn certifications only. While theoretical knowledge is certainly required to become a good data science professional, recruiters don’t put much emphasis on certifications only. Instead, they tend to evaluate the potential of a candidate by going through his/her work.
If you’re interested in learning artificial intelligence or machine learning or deep learning to be specific and doing some research on the subject, probably you’ve come across the term “neural network” in various resources. In this post, we’re going to explore which neural network model should be the best for temporal data.
Being a data analyst would mean you’ll have several skill-sets that one needs to work in the domain of data science. However, it doesn’t mean you can easily jump from your data analyst career into the role of a data scientist. Before discussing if being a data analyst could act as a step to becoming a data scientist, let’s take a look at what each of these professionals do.
From businesses and government institutions to non-profit organizations, there is a seemingly-infinite quantity of data that can needs to be sorted and interpreted to get information that can be applied for a wide array of purposes. With “big data” being the buzz word these days, pursuing a data scientist career has become one of the hottest trends of modern times. Whether you take up a full-time data science course or opt for a data science bootcamp in Silicon Valley, you’ll need to known certain trending technologies (as mentioned below) to make a mark in this field: