Why and What Made Companies to Adopt Machine Learning

Why and What Made Companies to Adopt Machine Learning

Sreenivas T
August 13, 2019
235 Views

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Machine learning is not a mere fact of technological elevation anymore as it reached the invincible heights like never before. The radical change in the business is made possible with the booming revelation of Machine learning technology. Though the technology is elusive and not evolved completely, tech minds still believe that ML can ameliorate the business values.

Many users immersed in the world of Machine learning such as Siri, Cortana, Google maps, e-commerce platform without any proper realization. The challenge lies in figuring out the exact use cases in the Machine learning platform. The deep understanding of adopting Machine learning is on a harder note but companies know the value factor of ML tools.

While the potential for ML is enormous, implementation is wearisome for the key reason for personal access. Machine learning is still especially a coding speciality, requiring systems, for example, TensorFlow, Caffe, and Spark MLlib, all of which need solid information. The confined hiring pool moderates the capacity for the knowledge to spread.

This problem does not impose any fear factor in Machine learning.  ML adoption will primarily come from two areas that may be tech giants willing to pay to build a group of code geeks, startups where a small group of Machine learning people can focus on specific areas.

Factors that make the companies choose Machine learning

High-end platform

Cloud technology provides the cutting edge factor for Machine Learning in the means of hardware and personalization options. Considering the fact of its process capability, companies showing a greater amount of eagerness to establish a Machine learning platform in the day to day business approaches.

Data processing

Data processing is the task that involves an innumerable amount of hardships to maintain. Cloud computing enables data processing in a quicker and efficient way. It can also be used to arrive at a clever decision as it facilitates deep security and remote functioning capability.

Customer support

Deriving customers is the main aspect of any business technologies and it can be possible only by enabling unparalleled customer support. Business seeking to retain the customer highly relying on a Machine learning algorithm. The algorithm perfectly analyzes the minds of users and then respond to customer queries in the quickest possible way. Users also feel more convenient to converse with chatbots instead of a human.

User acquisition

Any enterprise business includes three basic scopes such as making the users understand and demand their needs, displaying relevant products at a suitable time and maintaining intense engagement throughout the order flow. Machine learning contributes immensely to the support of user experience for enhanced brand value, promotion and copy. Even the research is under process to improve the user conversion rate by sending E-mail at the able time.

Business forecasting

Forecasting is the inevitable element in the business sector to make predictions such as demand, capacity, budget, and revenue. Inventory and sales platform adopting Machine learning in a faster way to meet the exact demand and not to fall short of supply. Sheer examination of the sales force can be monitored with the integration of Machine learning. Business giants like Walmart use Machine learning to drive sales by feeding set of historical data. Insurance companies rely on ML to predict user claims and outcome possibilities.

Security

Paying close attention to fraudulent intents in the online platform is troublesome for any conglomerate. Machine learning arrived in a spectacular fashion to intelligently monitor all the transactions in real-time. PayPal introduced Machine learning models to signal the fraud alarm and have omitted the false transaction by 50% considerably.

Adoption of Machine learning in leading tech companies

Pinterest

The fascinating place to save, upload, manage images known as pins in the era of social media culture. The adoption of technology leads to proper curation of the content. This made the Pinterest to seize the Machine learning company called Kosei for content discovery, recommendation algorithms.

The app finely evolved with the use of ML which carries out business operations, spam moderation, content discovery, and e-mail newsletters. Machine learning not only understands the subject of the image but also match them with other visual patterns. Categorizing and curating, predicting engagement, prioritizing local interests also feasible with ML.

Twitter

The irreplaceable tool in knowing and following world trends. Image handling is a tedious process as someone posts a photo, the thumbnail should be visible to click that image. Twitter sorted this issue by employing neural networks that make the image very appealing.

Twitter algorithm displays tweets based on the user recommendation in a chronological timeline pattern. Thus twitter applying a Machine learning tool to notifications to show you the best tweets, hot topics in the medium, and similarly many services by with standing relevancy in the timeline.

Facebook

Facebook employs Machine learning tools for ranking, classification, and content curating services. Facebook messenger has become a convenient platform for testing the chatbots as any developer can build and deploy a chatbot here. The company is looking for an algorithm that can read images to blind.

The work of ML not finished yet as it also involves showing news feed, serving ads, search, classified feeds, figuring the people’s images, translation of many languages from country to country in a simple and accurate manner.

Alibaba

Undoubtedly, one of the leading online e-commerce platform in the world. With over 500 million users of Alibaba, each user specifies different products. To streamline the process of listing and buying items, Machine learning can be effectively employed.

Machine learning keeps the user engaged each time and learn from each transaction to stay updated with the data of customer needs. Ali Xiaomi, a personal chatbot made for managing the user inquiries in written and spoken formats.

Yelp

The most amazing platform for the city-dwellers as they can get a hint of recommendations for famous dine-ins, nightlife, entertainment, and so on. It adopts the Machine learning for categorizing popular dishes on the restaurant profile. Yelp shows the detailed page containing the price, menu and latest reviews.

Yelp implements the picture classification technology to accumulate, process and lists the image. Seamless User interface enabled by image processing with the help of Machine learning.

IBM

The tech giant still maintaining the legacy but never failed to endorse themselves in the modern paced technologies. It has developed a Machine learning tool called IBM Watson which is an irrevocable element in the hospital to make accurate and clever decision making in cancer diseases.

IBM Watson also finds unbeatable position in the retail and e-commerce platform to help customers. It also empowers the multi cloud platform in a seamless manner to maximize resource utilization.

Google

The ocean of information at your disposal in a single platform. Google redeems itself in recent years to contribute vast majority of fields such as medical, neural networks, and so on. The company is researching the deep network algorithm patterns that leads to development in neural networks, natural language processing, speech translation, and search rankings. 

Conclusion

It would be a misstep to view Machine learning as some sort of corporate panacea—at last, the presentation of an ML framework is just on a par with the information on which it is prepared, and a venture’s key choices are regularly “edge cases” that require a proportion of human judgment and narrative experience to survey.

Rather than being astonished by the unique capability of Machine learning, officials should approach the subject of putting resources into this innovation by checking out their core business challenges and coordinating them against the key ability of Machine learning: drawing sense and significance from a huge amount of information. Given the assorted variety of contextual investigations over, the chances that Machine learning systems can help might be more noteworthy than you anticipate.

About Fusion Informatics

We, Fusion Informatics as a Top Machine learning development companies in Bangalore, Ahmedabad, Mumbai, Delhi, Noida and Gurgaon is conscious of the significance of Machine learning and its boisterous capability towards the advancement of the future. Fusion Informatics holds a string of experts striving upright for the challenges in technology. We take extreme concern about the client needs throughout the developing process. We are leading destinations for varied industries in curating Machine learning that will serve the company in the distant future. We are highly motivated and dedicated to the necessity of satisfying clients through our solutions.

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