Learn The Evolution of Data Science- From AI to ML
Table of Contents
Data science is a discipline that draws from various fields of study, including artificial intelligence (AI), machine learning (ML), and statistics. The goal is to extract insights from large amounts of information, which you can use in various applications.
Data scientists work with large datasets to solve complex problems by applying techniques based on these fields of study. In this post, we'll explore the evolution of data science from AI to ML so you can better know what it means to be a data scientist today!
An Introduction to AI
AI refers specifically to technologies created using various approaches derived from machine learning techniques—for example, deep neural networks (DNNs), reinforcement learning agents such as neural networks with associative memory and temporal difference methods—and evolutionary algorithms such as genetic algorithms (GA).
AI is used in various industries and has become a vital part of our society. For example, AI is used in healthcare to help diagnose diseases, improve patient outcomes and reduce costs. In agriculture, it's used to monitor crops and detect disease before it spreads.
In education, it gets used as an assessment tool for students or teachers who need help with specific skill sets such as computational thinking or problem-solving. You can also apply this in transportation (for example, autonomous vehicles), financial services (credit scoring), or other areas where humans interact closely with machines.
An Intro to Machine Learning
ML is an approach to artificial intelligence (AI) in which computers learn without being explicitly programmed using statistical models based on historical data or user input. Machine learning uses algorithms that make decisions without human intervention or explicit programming instructions; its goal is to solve complex problems without requiring human intervention at every step.
The Evolution of Data Science- From AI to ML
The evolution of data science has been an exciting ride. From the early days of artificial intelligence (AI) to machine learning and deep learning, we have seen many advances in AI and ML over the past few decades.
The next level of evolution will get driven by another technology: artificial intelligence, or AI. We are already seeing some of the first signs of this new development.
Data science is an interdisciplinary field that draws upon principles from computer science, mathematics, statistics, physics, and engineering to help us understand the ever-increasing volume of data produced by our society.
Artificial Intelligence has been around for years, but it wasn't until recently that machines could outperform humans in certain areas. The use of deep learning (DL) had enabled AI algorithms to make big leaps forward in accuracy and speed since 2015 when Google released DeepDream. This image recognition toolkit uses convolutional neural networks (CNN) trained with large datasets as part of its machine learning pipeline process recognition tasks such as image classification.
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