Machine Learning in Space

Machine Learning

Machine learning refers to an application of artificial intelligence, which offers the system with an ability to learn automatically and improve based on experience without the need for a complicated program. The main focus of machine learning is the development of computer programs, which can have accessibility for data and use it to lean with human assistance or intervention, after learning they adjust accordingly based on instructions (Robert & Christian).

Vendors in Data Science and Machine Learning

There are various vendors in data science as well as machine learning. Based on research, Immuta and DimensionalMechanics are among the leading vendors in the machine learning space. They have some features, which make their products appear useful and unique. Besides, based on this technology, the management offers quality products and services to all the clients.

DimensionalMechanic's New Approach

The management of DimensionalMechanic has set up a platform for data science, which breaks from the market traditions as well as the culture of doing things the same way. For instance, conventional vendors have developed notebook based or workflow based science environment, which is not as effective as it used to be. The DimensionalMechanics have developed a data science metalanguage. In regard, it has been able to come with new approaches and algorithms to unusual kind of data such as video, images, and sound that have become more deployable and accessible. In regard, DimensionalMechanics low code enhanced better understanding of the business and customers' needs. It is possible to customize the low code automated deep learning capabilities for content, data, video, photos, biometric and any other data form factor.

Immuta's Data Management Platform

Immuta provides a management platform and dedicated data access for the development of machine learning, automation policy enforcement as well as other advanced analytics. The products serve as a control layer whose role is to control and connect the access between the heterogeneous array of data science tool and myriad data sources without the need to copy or move data. The effectiveness of this approach is to address the expectation of the market that the platform, which supports the data science, will highly be extensible and flexible to the toolkit and data portfolio of the users' choice.

Advancements in Machine Learning

Machine learning is advancing at a fast rate. However, the approach for data management is holding it back. With Immuta, it is possible to make the data discoverable without necessarily copying or moving it. Any tool can be connected directly to Immuta by data scientists. Besides, the governance professionals can come up with a condition based policies, which dynamically apply to the data and the outcome is excellent. More accurate models deploy with greater durability, less business risk, faster and with more powerful insights (Witten &Ian).

Rapid and Unified Data Access with Immuta

Immuta empowers one with personalized and quick access to data to simplify and accelerate every aspect of workflow analysis. It is possible for the data scientist to work together through Immuta and in a unified data environment, which enables them to have quick accessibility of siloed datasets with action thoroughly audited. Moreover, the Integrated Data Control Plane at Immuta provides a single simplified interface that helps to monitor and manage enterprise analytics. The management has a platform that provides an opportunity for the user to connect from a storage system to virtual catalog that is quite simplified. In regard, it provides the users with rapid as well as self-service data accessibility without losing insight or control into manner in which the data is used.

Competitive Advantage and Intelligent Decisions

The organization applying machine learning technology has a competitive advantage since they can be able to overcome any challenges that stand between them and the achievement of their goals. They provide an opportunity for the business where they are applied to make accurate and quick decisions that will enhance the operation of the business such that the customers will be much satisfied. Based on the growth of smart algorithms, Business Analytics have an opportunity to move beyond Predictive and Descriptive, a scenario that will enable most organizations to realize their vision with much ease. Machine learning will also help the management to make intelligent decisions along with the capability to note the data that is no longer important. Hence it is eliminated to keep from causing more problems later.

Machine Learning in Space

Machine learning in space help in resolving the challenges that associated with traditional scheduling software, which is operated by a man, some issues emerge as a human being is operating which are resolved by machine learning. Hence, it makes works easier, and its output is more uniform and presentable. Therefore, it should be adopted in large number due to its capability executing programs that are central to the development of an organization (Bottou & Léon).

Embracing Machine Learning for Growth

It is apparent that Machine Learning is one of analytics technology that has the potential to change many organizations to enhance their services, despite its technicalities as well as advanced programs, it is important to familiarize with it as an organization management so that they can tap on its potential in the growth and development of a company. There should be experts and professionals in every organization whose role is to finds for ways and means for application of this technology.

Work cited

Witten, Ian H., et al. Data Mining: Practical machine learning tools and techniques. Morgan         Kaufmann, 2016.

Robert, Christian. "Machine learning, a probabilistic perspective." (2014): 62-63.

Bottou, Léon. "From machine learning to machine reasoning." Machine learning 94.2 (2014):        133-149.