AI (Artificial Intelligence) and ML (Machine Learning) are two related fields of computer science that are concerned with the development of systems that can learn and make intelligent decisions.
AI is a broad field that encompasses several subfields, including natural language processing, robotics, and computer vision. The goal of AI is to create systems that can perform tasks that would normally require human intelligence, such as recognizing patterns, understanding language, and making decisions.
Machine learning is a subfield of AI that is concerned with the development of algorithms and models that can learn from data. Machine learning algorithms are designed to improve over time as they are exposed to more data, and they can be used to perform tasks such as image recognition, speech recognition, and natural language processing.
There are several types of machine learning algorithms, including:
1. Supervised learning: At CodTag, In supervised learning, the algorithm is trained on labeled data, where the desired output is already known. The algorithm learns to map inputs to outputs based on this labelled data.
2. Unsupervised learning:In unsupervised learning, the algorithm is trained on unlabeled data, and must learn to find patterns and structure in the data on its own..
3. Reinforcement learning: In reinforcement learning, the algorithm learns through trial and error, receiving feedback in the form of rewards or punishments as it interacts with an environment.
AI and ML have many applications in various industries, including healthcare, finance, and transportation. For example, AI and ML can be used to analyse medical data and identify patterns that can help doctors to diagnose and treat diseases more accurately. They can also be used in the finance industry to detect fraud and manage risk, and in the transportation industry to improve safety and optimise traffic flow.