Machine Learning basics
Machine Learning is a technology that primarily deals with the functioning of the machine on the basis of the decision making, the feature which is offered to the machine through the machine learning technology which means the machine is able to make decisions on its own without any supervision of a human being. This is a great innovation and advantage for the humans as they don’t need to be always there by the side of the machines to operate them and they can invest their energy and time to other concerned tasks. Whereas blockchain is the technology that is being used to perform the process of transaction between different participants or users which is secured and trustworthy.
Machine Learning and Blockchain- Worth technology or not
There are many advantages of using these types of technologies as these technologies are helping in decreasing the workload of the humans and making all the working process more secure and efficient as in the case of financial sectors there will be no use of any kind of intermediate user or middle people like various government or private agencies. Therefore, adopting these new technologies has made a great change in the working pattern of such authorities and sectors. Machine Learning and Blockchain are widely used in financial sectors because machine learning uses the huge amount of information or data determine the hidden pattern inside a complete set of data and this helps in designing an improved and efficient system which uses its past mistakes and analyze the previous set of data to learn the things which are needed to be corrected by its own and this makes the machine to learn new working patterns and operations to be carried out of that machine without any mistake. Some of the machine learning systems are tracking software, voice recognition software, self-driving vehicle, fitness armbands, and many others. Whenever the machine learning software gets in touch with a new information, then it gets adapted to such kind of information and uses that information when the data resembling and that information is collected or received. For example, if you receive a message from a particular sender or user and mark it as a spam then whenever the message is received from that sender or user that system will automatically mark the newly received message as a spam. There is various software development company that works on advanced machine learning algorithms and they are better and efficient as they perform more research and operations on their datasets. And therefore, all this is beneficial to use in financial sectors as this is a kind of sector in which you cannot afford to make mistakes. Hence, a combined use of machine learning and blockchains are helping the experts in making the financial sector a sector with top secured features and efficiency. Because blockchain is among the world’s most secured databases as it offers great features like permanent storage, data in a pattern of decentralized ledger along with its time-stamped instances. It uses the digital fingerprints along with a consensus mechanism in order to generate the digital ownership for the collected data on the blockchain. The resulted data is completely decentralized ledger and this cannot be detected by any censorship of the government or any other intermediate body. Therefore, all these qualities and features make the blockchain a great technology that can store confidential or sensitive information and data which is very precious and can be used in a wrong manner if stolen by any malicious organization.
What’s best about the combination?
The combined use of machine learning and blockchains makes the best technology which is used to build models for accurate predictions and carrying out the right actions. Further innovation with all the data collected should be organized and audited for accuracy. The financial sector is an area that has to be improved with the use of these technologies. By using such secured tools, data can be transferred directly and reliably from one place to the another. This is allowing the companies to work on their decisions to improve and provide the results in a more accurate and estimated manner. Both these technologies are a great game changer for the finance sector as their self-driving research in depth is creating a marketplace for data scientists to conduct their research and make this world a whole new and better world to live.
