The Development of Data Science Throughout History
Data Science is a rapidly growing field, made even more so with the advances of Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL). Data Science in the 1950s and 1960s was focused on discovering hidden patterns from data. It wasn’t until the 1970s to 1990s when data scientists started exploring how to use computers to do predictive analytics. By the start of the 21st century, AI, ML, and DL technologies had evolved significantly, enabling breakthrough applications across various fields.
Today, AI, ML and DL are playing a major role in data science. AI and ML applications can be used to process large datasets faster than ever before. They also enable us to automate analytics processes such as automating feature engineering or hyperparameter optimization. Moreover, deep learning models allow us to build sophisticated models that can understand complex problems like natural language processing or computer vision tasks with greater accuracy.
The ability of deep learning models to learn without explicit programming has pushed our understanding of data science far beyond what was possible even a decade ago; it’s revolutionizing how we analyse data and solve complex problems with machines. As it continues to advance, we will see AI, ML and DL increasingly used in tandem with traditional analytics techniques for many more use cases in business operations and decision making.