AI Algorithms
List of AI & ML Algorithms as a quick reference 1. Deep Learning Algorithms 2. Reinforcement Learning Algorithms 3. Supervised Learning Algorithms 4. Unsupervised Learning Algorithms 5. Semi-Supervised Learning Algorithms Deep Learning Algorithms | Read 1. Neural Networks Backpropagation algorithm | Read 2. Feedforward Neural Networks (FNN) | Read 3. Convolutional Neural Networks
AI Algorithms
Single-shot detectors, often abbreviated as SSDs, are a type of object detection model used in the field of artificial intelligence (AI) and machine learning (ML). They are designed to efficiently and accurately detect and locate objects within images or video frames. SSDs are known for their speed and ability to
AI Algorithms
Graph Neural Networks (GNNs) are a class of artificial neural networks designed to work with structured data represented as graphs. A graph neural network (GNN) is a type of artificial neural network that is designed to process graph data. Graphs are a powerful way to represent data with relationships between
AI Algorithms
A Generative Adversarial Network (GAN) is a class of artificial neural networks used in artificial intelligence (AI) and machine learning (ML) for generative tasks. GANs were introduced by Ian Goodfellow and his colleagues in 2014 and have since become a fundamental and powerful tool in the field of deep learning.
AI Algorithms
A Restricted Boltzmann Machine (RBM) is a type of artificial neural network used in artificial intelligence (AI) and machine learning (ML). RBMs are a type of generative stochastic artificial neural network that can learn a probability distribution over its set of inputs. They are particularly well-suited for dimensionality reduction, feature
AI Algorithms
A deep belief network (DBN) is a type of artificial neural network that is composed of multiple layers of hidden units, with connections between the layers but not between units within each layer. DBNs are trained to learn a hierarchical representation of the input data, with each layer learning to
AI Algorithms
A Recursive Neural Network (RecNN) is a type of neural network architecture used in artificial intelligence (AI) and machine learning (ML) for tasks involving hierarchical or tree-structured data. Unlike traditional feedforward or recurrent neural networks that operate on sequential or grid-like data, RecNNs are designed to process and analyze data
AI Algorithms
A Recurrent Neural Network (RNN) is a type of artificial neural network designed for processing sequences of data. Unlike feedforward neural networks, where information flows in one direction from input to output, RNNs have connections that loop back on themselves, allowing them to maintain a hidden state or memory of
AI Algorithms
A Convolutional Neural Network (CNN) is a class of deep neural networks designed primarily for processing and analyzing visual data. CNNs are a foundational technology in the fields of artificial intelligence (AI) and machine learning (ML), particularly in computer vision applications. They are highly effective at tasks like image recognition,
AI Algorithms
Transformers are a type of architecture in artificial intelligence (AI) and machine learning (ML) that has had a significant impact on various natural language processing (NLP) tasks and other sequence-to-sequence tasks. They were introduced in a 2017 paper titled "Attention Is All You Need" by Vaswani et al.
AI Algorithms
A Feedforward Neural Network (FNN), also known as a feedforward neural network model or simply a feedforward network, is a fundamental type of artificial neural network used in machine learning and artificial intelligence. It represents the simplest form of a neural network, where information flows in one direction: from the
AI Algorithms
Recent innovations like LaMDA, PaLM and GPTs are based on Large language models (LLMs) or Transformer-based language models (TLMs) and developed by Google and OpenAI. LaMDA: LaMDA means “Language Model for Dialogue Applications”. LaMDA (Language Model for Dialogue Applications) is a family of conversational large language models (LLMs) developed by