Obtaining the AWS Machine Learning Specialty Certification is a demanding but highly rewarding achievement for data science and machine learning professionals. While many pursue other AWS certifications first, attaining this certification without prior AWS experience is entirely feasible.

It is useful for a data science practitioner to understand how to apply clustering algorithms due to their ability to discern and group similar data points without prior labeling knowledge. Clustering is instrumental in revealing hidden patterns within data, aiding in customer segmentation and anomaly detection applications.

Prototyping new models can be a time-consuming process. It combines business understanding, data understanding, data preparation, model creation, and evaluation. Luckily, there are a few ways to speed up the process to enable fast decision-making in a business setting.

Supervised machine learning is a branch of artificial intelligence that involves training algorithms to make predictions or classifications based on input data. We have a labeled dataset in supervised learning, meaning we have input features and corresponding output values. The goal is to train a model to predict output values for new, unseen input data accurately