Machine Learning and its application to Big data
Given the continuous process of evolution and digitization that society is going through, new hardware, strategies and transformations are being created every day. One of them is the data sector, that is where very useful applications such as Machine Learning and Big Data come from.
Companies are now more interested in these techniques and on how to use them. This is done with the purpose of extracting knowledge from data and to obtain, this way, an advantage over competitors in the market. Within the Big Data universe, specifically, in the data science world, Machine Learning techniques is becoming relevant taking a leading role, these two are leaving a mark in history and are going to become a key element in the near future.
The advanced analytics of Machine Learning together with the use of Big Data
When speaking about Machine Learning and Big Data there are a lot of interrelated concepts between them, however they have a different scopes or objectives. Machine Learning is capable of learning by itself from situations, patterns or characteristics contained in the information and to use that knowledge from that moment on. The more information there is and the more reliable data is, the better it is for the learning process.
Machine Learning is able to generate knowledge and to create smart actions from what has been learned. These smart actions get better with time becoming more precise.
Big Data, also known as advanced analytics, is used to determine important information and to correct processes. This technology is able to obtain a very effective impact on the entire company’s chain of value. The analytics is capable of recognizing big volumes of data from different origins and formats. It is capable of utilizing these statistical models, as well as other mathematical tools to get assessments or analytics that contribute to the improvement of operations or other actions in a weighted way.
When knowing about Machine Learning, consumers choose this tool to use it with Big Data, through advanced analytics. It also grants them the opportunity to filter specific characteristics, as well as to affirm the company’s capacity to offer what customers really look for.
How does Machine Learning work?
Machine Learning grants the necessary autonomy to computerized systems so that they learn from mistakes and improve from success. The final end is to establish the individuals that manage to be automated and spread efficiency, which do not require continuos programming.
Machine Learning is a system that identifies complex schemes from enormous information volumes, processing them to forecast behavior. The content to be optimized allows it to develop its own models to formulate choices, without any external help. Machine Learning helps companies improve the customers’ interest follow-up, as well as market pricing.
Companies that operate Machine Learning to work using Big Data
It is very difficult to imagine an efficient Big Data that does not apply artificial intelligence technologies of Machine Learning. For big companies, which operate enormous quantities of data, analyzing the information manually is a tremendous and almost impossible task, for this reason they choose to use alternatives that help them to simplify the task.
Some companies such as Amazon handle Machine Learning to analyze their products and offer consumers what better adapts to their consumer profile. With this tool, they can predict the number of consumers who abandon their company to move towards competitors and study the reasons why that motivate these decisions. They measure the number of new consumers who meet their needs and their satisfaction level.
The Carlsberg Research laboratory, in Denmark, focuses on new products development applying top technologies. Because of this it has decided to use exponential technologies such as Machine Learning and Big Data algorithms. It uses advanced cloud and sensor systems to take the company to the top of the beer sector.
Another example is Netflix. Behind each suggestion or recommendation that is made where an automatic learning algorithm is hidden. This not only is positive for the customer, who uses this type of platform, but also for the company which has been saving a lot of resources.
Which Machine Learning tool to choose?
Some of the tools are:
- Spark MLlib:
As organizations accumulate major volumes and variety of information, more time is invested in its infrastructure. This tool has a general library of automatic learning: MLlib. It is designed to simplify, extend and to integrate easily with other tools. It provides a powerful and unified engine that is easy and fast to use.
It is capable of processing data transmission in real-time. The primitive Apache Flink concept is the high performance of processing frame and low latency flow. it admits processing by lots.
This is a new Apache Programming Establishment open code project. It has the essential purpose of making adaptable Machine Learning calculations that could be used under the Apache permit. It uses the engine recommendations through the user station, the data as a component and temperature as a preference.
It is a Python module of Machine Learning integrated with SciPy. Users can make a variety of tasks about different categories for example the selection of models and categories. It is being used by big companies in different industries for instance music transmission and hotels booking.
- . PyBrain
It is known for making programs work wit the minimum amount of code lines. It identifies and associates automatically data types and follows a nesting structure based on indentation.
Additionally, big companies choose their tools according to their needs and data capacity. It is all about knowing their demand in the market and the cost-benefit that will be obtained. It is recommended to determine which type of tool is needed exactly.
Finally, the Machine Learning usage along with Big Data is becoming more relevant in the wholesalers’ consumption markets. This causes that Machine learning is moving towards minor impact companies to guarantee its importance and supply market positioning. Qualified and capable professionals are required to keep up the fast pace at which technologies advance, those are each day more and more sophisticated, their presence in profession will increase in the labor world