Understanding the Data Side of Machine Learning

by Alyssa Meritt | May 21, 2022 | AI and Machine Learning

One of the primary goals of artificial intelligence (AI) and machine learning (ML) is to enable machines to learn and reason and, ultimately, to automate tasks or decision-making. However, while solution builders focus on decreasing the need for human intervention in...

The Machine Learning Workflow

by Alyssa Meritt | May 14, 2022 | AI and Machine Learning

The key components of any machine learning workflow are data collection, model training, and testing, and model error analysis. To ensure that your ML project is successful, it is important to pay attention to these steps carefully. The major bottleneck tends to...

What is Human in the Loop (HITL)?

by Alyssa Meritt | May 13, 2022 | AI and Machine Learning

Machine learning (ML) suggests that machines can learn and perform relevant actions without assistance from humans. However, to learn, machines must have data supplied by humans. Essentially, ML uses a set of data to predict an outcome. The most common association...

The Intricacy of Assessing Data Quality

by Alyssa Meritt | Mar 1, 2022 | AI and Machine Learning

Every AI professional agrees that the quality of training and testing data is of the utmost importance in machine learning. The better the quality of data, the better the performance of the machine learning algorithms. However, there is no common understanding of what...

What is Data Labeling?

by Alyssa Meritt | Jan 23, 2022 | AI and Machine Learning

In machine learning, data labeling refers to the process of tagging, annotating, classifying, moderating, transcribing, or processing raw data. Labeling data marks up your data to show your target the answer you want your machine learning model to predict. For...