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machine learning (ML)

Machine learning (ML) is a field of artificial intelligence (AI) where computer systems learn to perform tasks by analyzing data, rather than following explicitly programmed instructions. Most of today's AI systems today are powered by machine learning. Machine learning systems train predictive models on historical data to generate forecasts, which can then be used to make decisions.


These are some of the most popular and useful types of machine learning.


  1. Supervised Learning: This type of learning uses labeled datasets to train algorithms that can classify data or predict outcomes accurately[2].
  2. Unsupervised Learning: It involves using algorithms to analyze and cluster unlabeled datasets to discover hidden patterns or data groupings without the need for human intervention[2].
  3. Reinforcement Learning: A type of learning where an agent learns to make decisions by performing certain actions and observing the rewards/results of those actions[2].
  4. Semi-Supervised Learning: This approach combines a small amount of labeled data with a large amount of unlabeled data during training. The system is provided with some guidance on what to learn, but it also has the freedom to explore the data and learn on its own[5].

Applications of Machine Learning

Machine learning algorithms are used in a wide range of applications, including but not limited to:

  1. Social Media Features: Algorithms can personalize content feeds and suggest connections based on user behavior[3].
  2. Product Recommendations: E-commerce platforms use ML to recommend products to users based on their browsing and purchase history[3].
  3. Image Recognition: This involves identifying and classifying objects within images and is used in various applications such as medical imaging and facial recognition[3].
  4. Sentiment Analysis: ML can determine the sentiment behind text data, such as customer reviews, to understand consumer opinions[3].
  5. Healthcare: Algorithms can assist in disease detection, personalized treatment, and managing healthcare services[3].
  6. Finance: Machine learning is used for fraud detection, risk management, and customer service in the banking and finance sectors[3].
  7. Language Translation: ML enables the translation of text or speech from one language to another, facilitating communication across language barriers[3].


Citations:

[1] https://developers.google.com/machine-learning/crash-course/ml-intro

[2] https://www.simplilearn.com/10-algorithms-machine-learning-engineers-need-to-know-article

[3] https://www.simplilearn.com/tutorials/machine-learning-tutorial/machine-learning-applications

[4] https://www.tensorflow.org/resources/learn-ml

[5] https://www.geeksforgeeks.org/introduction-machine-learning/

[6] https://www.coursera.org/articles/machine-learning-algorithms

[7] https://builtin.com/artificial-intelligence/machine-learning-examples-applications

[8] https://www.reddit.com/r/learnmachinelearning/comments/vgtrsa/what_are_some_of_the_great_resources_to_learn/

[9] https://mitsloan.mit.edu/ideas-made-to-matter/machine-learning-explained

[10] https://www.geeksforgeeks.org/machine-learning-algorithms/

[11] https://www.javatpoint.com/applications-of-machine-learning

[12] https://alex.smola.org/drafts/thebook.pdf

[13] https://www.sas.com/en_gb/insights/articles/analytics/machine-learning-algorithms.html

[14] https://emeritus.org/blog/machine-learning-what-are-machine-learning-applications/

[15] https://www.digitalocean.com/community/tutorials/an-introduction-to-machine-learning

[16] https://machinelearningmastery.com/a-tour-of-machine-learning-algorithms/

[17] https://www.tableau.com/learn/articles/machine-learning-examples

[18] https://towardsdatascience.com/introduction-to-machine-learning-for-beginners-eed6024fdb08

[19] https://www.ibm.com/topics/machine-learning-algorithms

[20] https://www.geeksforgeeks.org/machine-learning-introduction/

[21] https://en.wikipedia.org/wiki/Machine_learning

[22] https://www.techtarget.com/whatis/definition/machine-learning-algorithm

[23] https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8822225/

[24] https://openlearninglibrary.mit.edu/courses/course-v1:MITx+6.036+1T2019/about

[25] https://www.spiceworks.com/tech/artificial-intelligence/articles/what-is-ml/

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