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- 02:28, 19 June 2024 Cloud Computing (hist | edit) [4,181 bytes] Wikinimda@home (talk | contribs) (Created page with "Cloud computing is a technology that provides on-demand computing resources over the internet. These resources include servers, storage, databases, networking, software, and analytics, which are delivered on a pay-as-you-go basis. Cloud computing allows businesses and individuals to access and manage these resources without the need for physical infrastructure, offering flexibility, scalability, and cost efficiency. Here are the main aspects of cloud computing: # '''Ser...") Tag: Visual edit
- 02:22, 19 June 2024 Edge Computing (hist | edit) [3,556 bytes] Wikinimda@home (talk | contribs) (Created page with "Edge computing is a distributed computing paradigm that brings computation and data storage closer to the location where it is needed, improving response times and saving bandwidth. This approach reduces the latency associated with sending data to centralized cloud data centers and is particularly useful for applications that require real-time processing and low-latency communication. Here are the key components and concepts of edge computing: # '''Proximity to Data Sou...") Tag: Visual edit
- 02:20, 19 June 2024 Internet of Things (IoT) (hist | edit) [3,355 bytes] Wikinimda@home (talk | contribs) (Created page with "The Internet of Things (IoT) refers to a network of interconnected physical devices that communicate and exchange data with each other and with other systems over the internet. These devices, often embedded with sensors, software, and other technologies, can range from everyday household objects to sophisticated industrial tools. Here are the key components and concepts of IoT: # '''Devices and Sensors''': IoT devices include a wide variety of objects such as smart home...") Tag: Visual edit
- 02:04, 19 June 2024 Big Data (hist | edit) [4,557 bytes] Wikinimda@home (talk | contribs) (Created page with "Big Data refers to extremely large and complex datasets that traditional data processing software cannot adequately handle. These datasets can be so vast and intricate that they require specialized tools and techniques to store, process, analyze, and visualize. Big Data is characterized by the "Five Vs": === 1. '''Volume:''' === * '''Scale of Data:''' Big Data involves massive volumes of data generated from various sources such as social media, sensors, transactions, l...") Tag: Visual edit
- 01:59, 19 June 2024 Data Storage (hist | edit) [3,896 bytes] Wikinimda@home (talk | contribs) (Created page with "Data storage in the context of artificial intelligence (AI) refers to the methods and systems used to save and manage the data that AI systems require for training, inference, and continuous learning. The data stored can include raw data, processed data, intermediate results, model parameters, and outputs. Effective data storage is crucial for AI applications as it impacts the performance, scalability, and reliability of AI systems. Here are some key aspects of data stor...") Tag: Visual edit
- 01:45, 19 June 2024 Machine Learning (hist | edit) [5,247 bytes] Wikinimda@home (talk | contribs) (Created page with "Machine learning is a branch of artificial intelligence (AI) that focuses on building systems that can learn from and make decisions based on data. Instead of being explicitly programmed to perform a task, these systems use algorithms to identify patterns, make predictions, or determine actions based on data inputs. Here are some key concepts and components of machine learning: # '''Data''': The foundation of machine learning. Data can come in various forms, such as tex...") Tag: Visual edit
- 07:42, 14 June 2024 START Success with AI (hist | edit) [1,746 bytes] Wikinimda@home (talk | contribs) (Created page with "'''START Success with AI''' is a structured methodology designed to help businesses effectively harness the power of artificial intelligence to achieve real-world results. Here's how it breaks out: '''S''' – '''Strategy''': Develop a clear plan for how AI will be used in your business. This involves understanding your goals, identifying the areas where AI can have the most impact, and setting a roadmap for implementation. '''T''' – '''Tactics''': Identify the speci...") Tag: Visual edit
- 11:49, 7 June 2024 Natural Language Processing (NLP) (hist | edit) [5,454 bytes] Wikinimda@home (talk | contribs) (Created page with "Natural Language Processing (NLP) is a subfield of artificial intelligence (AI) and linguistics that focuses on the interaction between computers and human language. It involves enabling computers to understand, interpret, and generate human language in a way that is both meaningful and useful. NLP combines computational linguistics, machine learning, and deep learning techniques to process and analyze large amounts of natural language data. === Key Components of NLP: =...") Tag: Visual edit
- 11:47, 7 June 2024 Deep Learning (hist | edit) [5,464 bytes] Wikinimda@home (talk | contribs) (Created page with "Deep learning is a subset of machine learning that focuses on using neural networks with many layers (hence "deep") to model and understand complex patterns in data. It is particularly effective for tasks involving large amounts of unstructured data, such as images, audio, and text. Deep learning has been instrumental in advancing artificial intelligence (AI) and has led to significant breakthroughs in various applications. === Key Concepts of Deep Learning: === # '''N...") Tag: Visual edit
- 11:46, 7 June 2024 Neural Networks (hist | edit) [5,810 bytes] Wikinimda@home (talk | contribs) (Created page with "Neural networks are a class of machine learning models inspired by the structure and function of the human brain. They consist of interconnected layers of nodes, or neurons, which process and transmit information. Neural networks are particularly powerful for tasks involving pattern recognition, such as image and speech recognition, natural language processing, and many other applications in artificial intelligence (AI). === Key Components of Neural Networks: === # '''...") Tag: Visual edit
- 11:44, 7 June 2024 Recommendation Systems (hist | edit) [5,246 bytes] Wikinimda@home (talk | contribs) (Created page with "Recommendation systems, also known as recommender systems, are a subclass of information filtering systems that seek to predict the preferences or interests of users and make suggestions for items or content that are likely to be of interest to them. These systems are widely used in various applications, such as e-commerce, social media, online streaming services, and content-based websites, to enhance user experience and increase engagement. === Key Concepts of Recomme...") Tag: Visual edit
- 11:41, 7 June 2024 Speech Recognition (hist | edit) [5,037 bytes] Wikinimda@home (talk | contribs) (Created page with "Speech recognition is a technology that enables computers and devices to understand and process human speech. This technology converts spoken language into text, making it possible for machines to respond to voice commands, transcribe spoken words, and interact with users through natural language. Speech recognition systems leverage a combination of acoustic models, language models, and various algorithms to interpret and understand speech accurately. === Key Components...") Tag: Visual edit
- 11:38, 7 June 2024 Computer Vision (hist | edit) [5,207 bytes] Wikinimda@home (talk | contribs) (Created page with "Computer vision is a field of artificial intelligence (AI) that enables computers to interpret and understand the visual world. By using digital images from cameras, videos, and deep learning models, computer vision seeks to automate tasks that the human visual system can perform. The goal is to give machines the ability to see, process, and analyze visual data in a way that mimics human vision, ultimately enabling them to make decisions based on this data. === Key Comp...") Tag: Visual edit
- 11:32, 7 June 2024 Predictive Analytics (hist | edit) [4,908 bytes] Wikinimda@home (talk | contribs) (Created page with "Predictive analytics is a branch of advanced analytics that uses historical data, statistical algorithms, and machine learning techniques to identify the likelihood of future outcomes based on historical data. The primary goal of predictive analytics is to forecast future events and trends, helping organizations make more informed decisions. === Key Components of Predictive Analytics: === # '''Data Collection''': Gathering relevant historical data from various sources,...") Tag: Visual edit
- 11:25, 7 June 2024 Quantum Computing (hist | edit) [4,533 bytes] Wikinimda@home (talk | contribs) (initial entry) Tag: Visual edit
- 11:10, 7 June 2024 Explainable AI (XAI) (hist | edit) [4,185 bytes] Wikinimda@home (talk | contribs) (initial entry) Tag: Visual edit
- 11:06, 7 June 2024 Edge AI (hist | edit) [3,465 bytes] Wikinimda@home (talk | contribs) (initial entry) Tag: Visual edit originally created as "Edge ai"
- 11:02, 7 June 2024 Federated Learning (hist | edit) [3,058 bytes] Wikinimda@home (talk | contribs) (initial entry) Tag: Visual edit