Machine Learning Algorithms: The world’s largest companies use this technology to understand user behavior better & make informed decisions.
Knowing how they use machine learning is one way to discover the potential of machine learning for your business. See some examples!
It is the most advanced company in the use of this technology. It has achieved this level through the in-house development of tools and techniques and the acquisition of startups.
At Google, machine learning is in several services, such as:
- Google Maps;
- Google translator;
- Google Search.
The company is also developing an autonomous car and has even conducted a conversation based on artificial intelligence. That’s Google Duplex, a Google Assistant feature.
The on-demand software company developed Einstein. Based machine learning analyzes and processes a large volume of data. In addition, it guarantees more accurate and profitable results.
This makes the work of sales and professionals in the commercial sector and call centers more efficient. At the same time, it also guarantees more profit for the company using the system.
The tech company has invested in machine learning for years. Also, in 2011, he presented Watson, a computer-based artificial intelligence. The equipment could read texts and answer questions. Now, it goes further and offers different services. For example:
- voice interaction;
- recognition and analysis of videos and images;
- creation of virtual assistants;
- reading large volumes of texts.
With a streaming service geared towards personalization, Netflix uses machine learning to make recommendations based on user preferences.
This increased subscriber satisfaction. Therefore, the company continues to do A/B testing and offline experiments to improve recommendation results.
It all started with the Siri voice assistant. Today, Apple also has other machine learning-based devices. This is the case with the Home Pod, which allows you to control the house through voice commands.
The credit card company uses machine learning to prevent fraud. This is because the technology identifies scams in real-time through data analysis. Thus, several data sources are adopted, such as:
- information about the holder;
- spending details;
- merchant information;
- identification of suspicious transactions.
In addition, American Express forecasts customer default rates. This way, credit limits are assigned according to this data and their analysis.
With all these examples and information, it is clear that machine learning is an essential technology for any business that wants to increase its chances of success. Having data, information and insights make it possible to make better decisions that can take your company to a new level.
So, if your startup still leaves machine learning aside, know it’s time to change this scenario. After all, this could be the opportunity to turn the tide and gain a competitive advantage, including expanding the business abroad and increasing market share.
How Does Machine Learning Algorithms Work?
The focus of this technology is to have data to analyze and learn from. Therefore, the more data fed into the systems, the more efficient the answers to existing problems will be.
Thus, the area seeks to evaluate the constructions of machine learning algorithms to extract patterns within a large volume of data. This way, the machine understands what it needs to do to perform complex tasks.
Machine learning algorithms consist of a sequence of precise actions that recognize and apply patterns to ensure machine learning. Therefore, each of them activates a command, and their set generates what is called machine learning.
In this way, the machine learns to make predictions, react to different situations and act intelligently. All based on data and experience gained.
For a company, machine learning is essential to add value and generate a competitive advantage. For example, this technology makes it possible to use statistical analysis to obtain more accurate answers and decrease the chance of errors.
At the same time, it becomes easier to detect fraud. Thus, banks and credit card administrators discover evidence of a scam in transactions. This prevents suspicious and fraudulent operations.
In addition, it is necessary to remember that the machine only performs what it is commanded to do. Upon reaching this level, several benefits are achieved. For example:
- agility in decision making;
- adaptability, as the data allows us to understand the current context and make the necessary adjustments;
- greater scope of objectives, which generates an algorithmic company that is, a company capable of innovating at high speed;
- gaining deeper insights ;
- efficiency in business processes;
Also Read: Where Can Machine Learning Be Applied?