Machine Learning

What is Machine Learning

Artificial intelligence (AI) is a growing service across the majority of industries today. Businesses have been embracing AI due to the logic, problem solving, learning and subsequent adjustments that benefit growth. A subset of AI is machine learning, which is focused on data, specifically statistical modeling techniques. Machine learning takes data, then learns from the data to identify patterns and make decisions. Machine learning requires the ability to build complex models from the ground up, and ensure the models work in complementary ways to automate processes.

Why is Machine Learning Important?

Machine learning enables us to analyze a large volume of complex data quickly to deliver accurate assessments.

What is a Machine Learning Workflow?

Machine learning is comprised of a workflow of data-oriented and model-oriented stages. The main stages of the workflow you can expect to undertake are:

  • Model requirements: Select which features to implement and what models will assist with the business problems at hand.
  • Data Collection: Identify existing datasets or which ones need to be created.
  • Data Cleansing: Ensuring inaccurate or irrelevant records are purged from the dataset.
  • Data Labeling: Data are labeled in order to bring them into the model.
  • Feature Engineering: The act of identifying which features to incorporate into the model.
  • Model Training: Models and their corresponding features are trained and updated.
  • Model Evaluation: This stage includes a feedback loop. Model evaluation measures the performance of the model against the end goal.
  • Model Deployment: The model is deployed and monitored for issues.
  • Model Monitoring: The last stage, model monitoring incorporates a feedback loop to ensure the model encounters no errors.

How Can I Incorporate Machine Learning Into the Business?

Whether you want to supercharge your supply chain, provide customized products for online and offline purchases, or connect and optimize systems early on, there are an endless number of ways to incorporate machine learning into your business.

 

To start, you'll want to document your current business processes. Any common process or decision can be automated by machine learning. For example, identifying fraudulent transactions or approving a loan would be good candidates for machine learning.

 

The next step is to find a partner to develop the machine learning solution in your business. As with most partnerships, speak to several experts to find the one that aligns with your needs. The major cloud providers such as Amazon Web Services and Google Cloud also offer machine learning services. Starting with the end in mind, once you identify the problem needing to be solved and the data available to be used, you’ve taken the first step in your machine learning journey.

Topics: machine learning, artificial intelligence