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ML Algorithm Explained: Naive Bayes
ML Algorithm Explained: Naive Bayes Naïve Bayes is a supervised machine learning algorithm, which predicts the class of a given data point based on features
ML Algorithm Explained: K Nearest Neighbors
ML Algorithm Explained: K Nearest Neighbours K-Nearest Neighbors (KNN) is a supervised machine learning algorithm, which predicts the class of a given data point based
Reshaping Entertainment with AI: Gaming
Reshaping Entertainment with AI: Gaming The gaming industry is constantly evolving and innovating to develop entertaining experiences for gamers. A core aspect of game design
Reshaping Entertainment with AI
Reshaping Entertainment with AI Technology is now an integral part of the entertainment industry. The proliferation of streaming platforms has permanently changed the traditional entertainment
Integrating AI into Automobiles
Integrating AI into Automobiles The automobile market is undergoing drastic changes as consumer focus shifts from form to function. Modern consumers are interested in electric
Leveraging AI in Agriculture
Leveraging AI in Agriculture The agricultural industry is facing the challenge of increasing food production to meet the demands of a growing global population. Agricultural
Frequently Asked Questions
Artificial Intelligence enables computer systems to use a combination of data, logic, and mathematical and statistical methods to solve problems and make decisions. It includes applications such as machine learning and cognitive learning, which is the most well-known application of AI.
Cognitive Learning enables computer systems to mimic human behavior when engaging in human interaction-related applications. A good example of AI is voice assistants found on many mobile devices and smart home devices.
ML enables computer systems engaging in data-related applications to learn from data in real time by employing statistical algorithms and techniques. A good example of ML is a search engine that uses data to identify the most relevant results when a user searches for something online.
Machine Learning Algorithms are formal statistical methods and processes to drive intended outcomes and generate predictions or forecasts. They use a series of mathematical steps to solve a data-related problem. There are many different types of ML algorithms for specific scenarios and applications.
The algorithm implemented directly impacts the quality of results that can be obtained from given data set. Therefore, applying the optimal algorithm is critical when utilizing machine learning.
Big data refers to large volumes of complex data that continue to grow over time. The data is composited at variable speeds and times from a wide range of sources in a variety of formats and the volume of data can range from terabytes to petabytes.
The main challenge is robustly processing big data within relatively short intervals of time (days, hours, real-time etc.). Due to complexity and ambiguity, big data is difficult to fully comprehend using traditional processes, which makes AI ML essential for businesses seeking to understand their data.
Data mining is a process of extracting meaningful information from large volumes of raw data. Data mining can identify patterns, trends, and connections in given data set based on certain criteria. Businesses can use insights from data mining in a variety of ways such as understanding customer behavior, designing effective marketing campaigns, and much more.