4MaL : Machine Learning for Machine Learning

What is 4MaL?

4MaL is a revolutionary new Machine Learning Micro-Service Application that gives you the tools you need to determine where you should spend your scarce machine learning resources.

What is Machine Learning?
Machine Learning is the process of training a computer to recognize complex patterns or make informed predictions based on provided information.

What are some examples of Machine Learning?

Example applications of Machine Learning include: identifying people in a crowd, classifying the sentiment of a customer on the phone, segmenting customers by behavior, and many other valuable tasks.

Why does my business need to use Machine Learning?

Your business will be able to reduce operational overhead associated with completing complex manual tasks, or enabling complex tasks you never thought possible because of the operational cost involved.

What is an example of a complex task which I could automate using Machine Learning?

One example of a complex task which you could automate using Machine Learning would be to determine the year on a coin, and thus its potential value. You could have a person complete this task, but the machine learning algorithm could complete this task faster and with greater accuracy.

What is an example of a complex task which I could enable using Machine Learning, but haven’t because of the operational cost involved?

An example of a complex task which you could enable using Machine Learning, but haven’t because of the operational cost involved, is analyzing surveillance video to determine and catalog which employees are gone from their desks, and for how long those employees are gone.

How would I use 4MaL?

First, you would connect 4MaL to all of your data, where 4MaL will mine all of your data to identify areas where your business may have some opportunities. Once these areas of opportunity are identified, 4MaL can analyze the data associated with those opportunities and determine which Machine Learning algorithms would have the largest impact to your business, and the highest likelihood for success. Next, 4MaL will provide to you the dependent and independent variables which your data science team can use to develop your machine learning algorithm. Once your team has built and trained your Machine Learning algorithm, you can include that algorithm into the Machine Learning Micro-Service Application (MaLMApp) architecture.

How does 4MaL work?

Quandant 4MaL starts by using a Machine Learning Algorithm to analyze and classify your data sets. Once your datasets have been classified, 4Mal uses another Machine Learning Algorithm to closely analyze your specific types of data sets, such as NPS score, phone call sentiment, and customer satisfaction surveys, in order to identify areas of opportunity for your business. Once these opportunities have been identified and quantified, you confirm which of these are true opportunities for your business. 4MaL uses another Machine Learning algorithm to pinpoint the factors that contribute to these opportunities and determine if the opportunity is predictable. If the opportunity is predictable, 4MaL uses yet another Machine Learning algorithm to determine which factors most contribute to this predictability. The output is a stack-ranked list of business opportunities, complete with most likely contributing factors, with which your data science team can use to build their Machine Learning algorithm.