Machine Learning

Machine learning is a subfield of artificial intelligence (AI) that focuses on the development of algorithms and statistical models that enable computer systems to learn and make predictions or decisions without being explicitly programmed. In other words, it is a set of techniques and approaches that allow machines to automatically learn from data and improve their performance over time. Machine learning The core idea behind machine learning is to build models that can recognize patterns and relationships in data, and then use those patterns to make predictions or take actions on new, unseen data. This is achieved through training, where the machine learning model is fed with a large amount of labeled data (input-output pairs) and learns from it to generalize and make predictions on new, unseen data. There are several types of machine learning algorithms, including: Supervised Learning : In this type of learning, the model is trained on labeled data, where the input data is paired

 Artificial Intelligence (AI) is a broad field of computer science that focuses on creating intelligent machines capable of performing tasks that typically require human intelligence. AI encompasses a wide range of techniques, algorithms, and approaches aimed at mimicking or simulating human intelligence in machines. Artificial Intelligence AI can be categorized into two main types: Narrow AI and General AI. Narrow AI (also known as Weak AI): Narrow AI refers to AI systems that are designed to perform specific tasks or functions within a limited domain. These systems are designed to excel at a particular task but lack the ability to generalize their knowledge or transfer their skills to other domains. Examples of narrow AI applications include voice assistants like Siri or Alexa, image recognition systems, and recommendation algorithms. General AI (also known as Strong AI): General AI refers to AI systems that possess human-level intelligence across a wide range of tasks and can auto