Why is ML the new-age solution to existing tech problems?

Machine Learning and Artificial Intelligence have become the most prominent technologies in the recent running years. A large number of IT and software giants such as-Google, Microsoft Azure and Amazon, etc. have emerged as the top players in this domain with an amazing Cloud-based Machine Learning platforms. But, most of us are experiencing the use of machine learning without actually knowing it. Most of the Facebook tagging and ‘Spam’ detection by email senders, etc. works based on the ML. This is how machine language has turned to be one of the most essentially needed solutions that add to the existing technical problems.

What Problems can be solved by Machine Learning?

Machine Language (ML) has proved significantly sound in solving many of the technically aligned jobs for solving the existing tech problems, such as-

Reduced Manual data entry

Inaccurate or duplicate data becomes a major business concern for every organization that wishes for an automated business processing. Use of machines language algorithms and other predictive modeling algorithms can be an amazing solution to this. These help in significantly improving the complex issues such as- calculations, performing time-intensive documentation and accurate data entry tasks.

Helps in Better Spam Detection

Spam detection has been the most currently solved issue using ML. Earlier pre-existing rule-based techniques were used for spam removal, however, currently, spam filters create can automatically create new algos for the process precision using ML. Technologies like- ‘neural networks’ in the spam filters have brought Google on the verge of lowering spams to around 0.1 percent. Spam detection on the social media websites is also being performed using the ML.

Product Recommendation

Most of the business operations have benefitted from ML models. The system has helped in supervised learning through a product based recommendation system that offers a complete purchase history, inventory of the products, etc. for both purchase and sales matters. This has proved to emerge as an amazing solution to the E-Commerce businesses.

Expert Help in Medical Diagnosis

Machine Language has proved to be an expert in the medical field for improving the patient’s health and minimize the medical costs, too. ML has helped in perfect diagnoses, best medicines recommendation, prediction and even identification of the high-risk patients.

Customer segmentation and LTV prediction

Customer segmentation, sales prediction, and lifetime value (LTV) prediction have been the major marketing challenges faced by any marketer. Combining data mining and machine learning, the data from various sources such as- email campaigns, website visits, etc. have been used for pursuing a data-driven accurate marketing approach.

Helps in Accurate Financial analysis

Dealing with accurate financial analysis with a huge volume of data of quantitative nature is a pretty difficult job. ML has helped in the accurate extraction of the data and further uses it for optimized financial analysis. Presently ML is used for a number of financial domains such as- algorithmic trading, fraud detection, portfolio management, and even loan underwritings.

Emerged as a pro in Predictive maintenance

AI and ML together have been used in manufacturing industries for identifying meaningful data patterns. These are further used in both corrective and preventive maintenance practices for both cost and efficiency maintenance.

Image recognition (Computer Vision)

ML has taken over computer vision that produces numerical or symbolic information extracted from the images and high-dimensional data. This is going to emerge as the most potential technology to be used for healthcare, driverless cars, arranging marketing campaigns, etc.

How is Machine Learning Applied to Various Business Problems?

• ML has been found to be well applied in almost every business domain and every existing problem for handling work associated with massive data.
• It has been applied to a number of ventures like- investment, conferences, and business-related works since 2012.
• A number of marketing operations, market analysis, etc. can be easily anticipated based on a perfect ML.

What Types of Business Problems Can Be Handled Using Machine Learning?

ML has proved to be effective in all niches of business including both inbound and outbound business operations. It is mainly due to the efficiency of the ML being capable of solving the business issue that the need for ML for solving the business problems has gone even higher.

Some of the major business problems that can be handled using ML are:-

Face detection

ML has given an incredible touch to the field of face detection world with allowing the machines to detect faces based on their facial expressions and hues. All this can be performed under the described algorithm based on ML.

Email spam filters

Spam filtration has been one of the biggest achievements that can be performed using the ML rules.

Recommendation of Product/ music/movie

Based on each person’s preferences, ML algorithms have the significant role in suggesting preferences to the audience with the changing over time. Amazon, Netflix, etc. make use of ML for such sort of functioning.

Speech recognition

Machine learning has the perfect ability to identify speech and voice patterns in order to help in the process of speech to text conversion.  This will simply revolutionize the business world. Nuance Communications is one of such popularly known speech recognition company, today.

Online advertising

ML helps in identifying the favorable patterns for publishing a particular ad on Facebook or Google. The algorithms under ML are capable of identifying the patterns in user behavior and thus help in determining the relevance of a particular advertisement for an individual user.

Fraud detection

Several frauds are spreading in the online world which makes it important to filter such frauds similar to the email spams. ML is introducing new fraud methods for system adaptability for higher real-time fraud detection.

ML has proved to be an efficient technical tool across varied industries. However, this requires highly qualified and well-versed data scientists or ML consultants to take over a particular business domain. ML will sooner or later bring a great change in the business world in terms of quick analysis, risk detection and higher data management. With rightly used ML algorithms all sorts of potential business problems are set to get resolved.