Data Analytics

Machine Learning: Logistics & Transportation {0}

By Thong N.

Machine learning is a big part of how businesses today operate and function. Once the technology is created and almost perfected, these machines that people create can make a big impact on how efficient a business operates. So far with the research and development that has been done on technology and machine learning, the need for more workers in the logistics and transportation industry will be a thing of the past. read more...

How Machine Learning has affected the Insurance Industry {0}

By Jose M.

Machine learning is a new type of “artificial intelligence” that gives computers an ability to learn, without being programmed. In our day in age, this is essential to all rapid technical advancements we are experiencing. One of the industries artificial intelligence is affecting is the insurance industry. read more...

Machine Learning in Aerospace {0}

By Louis M.

The aerospace industry is a complex and heavily data-reliant field which requires a great deal of research, design, and production for proper execution of its products and services. Machine learning has played an active role in the development of technology in aerospace to aid in this process, providing valuable information that would otherwise be difficult to obtain or unobtainable using traditional methods. The development of autonomous systems of control and execution for vehicles and aircraft has been a field of particular interest and help in this industry as well. As the development of this field progresses, it will continue to play a key role in the development of the industry as a whole. read more...

Machine Learning for Health and Medicine {0}

By Brian L.

The increasing power of computers have allowed for certain industries to grow tremendously and for new industries to blossom. This increase in computing power has given rise to a method of predictive data analysis and model building called machine learning. Through the use of complex algorithms, computers equipped with machine learning software are able to learn from past experience and data in order to produce reliable results and decisions. In many instances this has the effect of saving precious time and resources, as well as the ability to analyze such large and complex data that would be impossible for humans to do on their own. The implication of such abilities has changed the way many industries and businesses look to the future. The scope of my focus for this post will be the effect machine learning has had within the health and medicine industry. I will examine the benefits, applications and potential shortcomings of machine learning. read more...

Data Mining in the Insurance Industry {0}

By Angel M.

As the world moves towards an era of “Internet of Things” companies are trying to find different ways to produce accurate and effective information in the insurance industry. In the years, past client’s information was poorly documented on paper and was kept in folders and filing cabinets. Today, we can see a major transition of the same information being documented online and stored in databases or data warehouse for easier access. Tech companies have produced software such as, data mining tools that allow insurance companies to sort through their information within seconds. The process will allow insurance companies to cut down on insurance fraud and increase operational efficiency. read more...

How Government Services Are Using Data Technologies {0}

Nelly L.

We think of citizens as legally recognized subjects of a particular state or community. As citizens, they are bound to certain regulations and rules that are maintained and controlled by governmental agencies, who oversee every aspect of their lives for the well-being of the inhabitants as a whole. These government agencies control the economy, social freedoms, and political systems of the citizens. Unsurprisingly, they also take advantage of the most sophisticated business techniques today in order to do so. If that is so, how is business related to the government? And how does the government use data obtained from these business technologies to oversee citizen community engagement? read more...

Data-mining in Environmental Services {0}

By Jeremy K.

Data-mining for environmental services refers to any research or examination of large-scale data in relation to the environment. Some examples of environmental services that use databases are forecasting, ecosystems, and recycling. The benefits of data-mining in an environmental standpoint are to collect data and analyze the areas that directly affect the environment. In doing so, projects can be started in hopes of resolving the issues that negatively affect our economy. Analysis of such environmental factors can also allow us to improve the efficiency of certain aspects of the environment such as how to make traffic flow smoother. Benefits of datamining in environmental services also include efficiently analyzing issues that arise through cluster diagrams and determining the best option through regression models and various software technologies. Data-mining in environmental services can also help influence the health industry through new discoveries of habits that cause certain diseases such as cancer. read more...

Data mining in Entertainment {0}

By Malcolm I.

The entertainment industry is always evolving to keep up with fans, ratings, and sending information to viewers. With today’s technology it makes entertainment easier to access from viewers without any technical difficulties. Big data is there to help make things easier for the industry. Data mining in the entertainment industry is sometimes used to give insights on what the audience really wants. The information they receive can help expand a show already on the air or help develop new ones (Rijamen, M. V.). Big data also helps the entertainment industry understand whether a movie or series will be a hit. read more...

Machine Learning in Environmental Sciences {0}

By Patrick K.

Environmental sciences have utilized machine learning in various ways from tracking weather patterns to predicting animal behaviors, much of this is created using R. Though, niche, environmental sciences utilizes machine learning in what many would see as unconventional. Two examples of machine learning in environmental sciences are The Biodiversity and Climate Change Virtual Laboratory (BCCVL) and DIVA-GIS. DIVA-GIS specializes in studying biodiversity and mapping out/predicting the area pointed out. For example, DIVA-GIS is used to predict climate in a certain area based on data given to the software. With this, researchers and other institutions can determine where certain species can exist or will potentially go to depending on the data given. (Hijmans, 2017) read more...

Machine Learning in Financial Services {0}

By Aaron L.

One of the two big driving forces of leading edge technological advancements is machine learning, while the other force being big data. Machine learning can be thought of as a sub-discipline of AI where people can feed data to a machine, and the machine will be able to analyze the data to make the best possible decision. In this post, I will be discussing machine learning specifically dealing with financial services. There exist several machine learning applications to present day financial services. The current machine learning applications towards financial services are but not limited to automated portfolio management, fraud detection, and risk management. read more...