How the Bigdata and ML You Need to Solve Data Problems

Bigdata and Machine Learning are helpful for your analytics career. The reasons are simple. You will see how these are related.

To solve Big data problems, you need Machine learning and Tools and Software technologies involved in developing Machine Learning frameworks and algorithms.

How do you say Big data is increasing

We are entering the era of big data.

For example,

there are about 1 trillion web pages. One hour of video is uploaded to YouTube every second, amounting to 10 years of content.

The real-time example is Walmart handles more than 1M transactions per hour and has databases containing more than 2.5 petabytes (2.5 × 1015) of information.

Where Machine Learning comes

This deluge of data calls for automated methods of data analysis is what machine learning provides.

In particular, we define machine learning as a set of methods that can automatically detect patterns in data and then use the uncovered ones to predict future data or to perform other kinds of decision-making under uncertainty (such as planning how to collect more data!).

The best way to solve such problems is to use the tools of probability theory. The probability theory you can apply to any uncertainty.

In machine learning, uncertainty comes in many forms: what is the best prediction about the future given some past data?

What is the best model to explain some data?

What measurement should I perform next? etc.

The probabilistic approach to machine learning is closely related to the field of statistics.


Author: Srini

Experienced software developer. Skills in Development, Coding, Testing and Debugging. Good Data analytic skills (Data Warehousing and BI). Also skills in Mainframe.