{"id":1736,"date":"2019-06-03T03:34:01","date_gmt":"2019-06-03T03:34:01","guid":{"rendered":"http:\/\/kusuaks7\/?p=1341"},"modified":"2023-06-23T12:44:08","modified_gmt":"2023-06-23T12:44:08","slug":"a-non-technical-guide-to-understanding-machine-learning","status":"publish","type":"post","link":"https:\/\/www.experfy.com\/blog\/ai-ml\/a-non-technical-guide-to-understanding-machine-learning\/","title":{"rendered":"A Non-Technical Guide To Understanding Machine Learning"},"content":{"rendered":"

In the last\u00a0post<\/a>, we discussed if machine learning was right for your business. As part of that effort, I recently went through the process of learning the ins-and-outs of machine learning and realized most information out there is technical and aimed at developers or data scientists.<\/p>\n

I thought an explanation from a non-technical person might be of interest.<\/p>\n

Let\u2019s begin.<\/p>\n

What exactly is machine learning?<\/strong><\/h2>\n

The simplest definition I came across: Machine learning is \u201c[…] the branch of AI that explores ways to get computers to improve their performance based on experience\u201d. Source:\u00a0Berkeley<\/a><\/p>\n

Let\u2019s break that down to set some foundations on which to build our machine learning knowledge.<\/p>\n

Branch of AI:\u00a0<\/strong>Artificial intelligence is the study and development by which a computer and its systems are given the ability to successfully accomplish tasks that would typically require a human\u2019s intelligent behavior. Machine learning is a part of that process. It\u2019s the technology and process by which we train the computer to accomplish the said task.<\/p>\n

Explores ways:<\/strong>\u00a0Machine learning techniques are still emerging. Some models for training a computer are already recognized and used (as we will see below), but it is expected that more will be developed with time. The idea to be remembered here is that different models can be used when training a computer. Different business problems require different models.<\/p>\n

Get computers to improve their performance:\u00a0<\/strong>For a computer to accomplish a task with AI, it needs practice and adaptation. A machine learning model needs to be trained using data and in most cases, a little human help.<\/p>\n

Based on experience:\u00a0<\/strong>providing an AI with experience is another way of saying – to provide it with data. As more data is fed into the system, the more accurately the computer can respond to it and to future data that it will encounter. More accuracy in understanding the data means a better chance to successfully accomplish its given task or to increase its degree of confidence when providing predictive insight.<\/p>\n

Quick example:<\/strong><\/p>\n

    \n
  1. Entry data is chosen and prepared along with input conditions (e.g. credit card transactions).<\/li>\n
  2. The machine learning algorithm is built and trained to accomplish a specific task (e.g.detect fraudulent transactions).<\/li>\n
  3. The training data is augmented with the desired output information (e.g. these transactions appear fraudulent, these do not).<\/li>\n<\/ol>\n

    \n

    How does machine learning work?<\/strong><\/h2>\n

    Machine learning is often referred to as magical or a black box:<\/p>\n

    Insert data \u2192 magic black box\u2192 Mission accomplished.<\/p>\n

    Let\u2019s take a look at the training process itself to better understand how machine learning can create value with data.<\/p>\n