AI & Machine Learning

Mathematics is foundational to understanding how neural networks work. Several key mathematical functions and concepts play a critical role in the design and functionality of neural networks. Here are some of the most important ones:

A Neural Network Network is a AI computational model inspired by the way biological neural networks in the human brain function It’s the backbone of most machine learning, particularly deep learning models. Key Components are

Machine learning frameworks provide tools and libraries that help the development, training, and deployment of machine learning (ML) models. These are popular machine learning libraries: Summary

Reinforcement Learning (RL) is a branch of machine learning where an agent learns to make decisions by interacting with an environment. The agent takes actions in an environment, receives feedback in the form of rewards, and improves its strategy over time. Unlike supervised learning, RL doesn’t require labelled data but learns from the consequences of…

Unsupervised learning is a type of machine learning where the algorithm is provided with data that is neither classified nor labelled, meaning the model learns from the data without explicit guidance. The goal is to uncover hidden patterns or intrinsic structures in the input data. Here are some common unsupervised learning algorithms: Applications of Unsupervised…

Supervised learning algorithms are a type of machine learning technique where a model is trained on labelled data. In this approach, each training example is associated with a corresponding output label, and the goal is for the model to learn the mapping from inputs to outputs. After training, the model can be used to predict…

Machine Learning (ML) is a subset of artificial intelligence (AI) that focuses on creating systems capable of learning from and making predictions or decisions based on data. Instead of being explicitly programmed to perform a task, machine learning algorithms use patterns and inference to generate insights. Here’s a detailed breakdown:

AI (Artificial Intelligence) is increasingly becoming a part of daily life, helping with tasks across a wide range of areas. Here are some detailed ways AI impacts everyday activities:

Key AI technologies that are driving advancements today include several fields of artificial intelligence. Here’s a breakdown of the major ones:

AI (Artificial Intelligence) encompasses various types and categories, each designed for different purposes and levels of complexity. AI can be classified into the following types: AI SubfieldsTo understand the different types of AI, it’s also important to recognize the subfields that contribute to AI development:Machine Learning (ML): This is the most prevalent subfield where algorithms…