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* [[Precision agriculture|Agriculture]]
* [[Automated theorem proving]]<ref>Bridge, James P., Sean B. Holden, and Lawrence C. Paulson. "[https://www.cl.cam.ac.uk/~lp15/papers/Reports/Bridge-ml.pdf Machine learning for first-order theorem proving]." Journal of automated reasoning 53.2 (2014): 141–172.</ref><ref>Loos, Sarah, et al. "[https://arxiv.org/pdf/1701.06972 Deep Network Guided Proof Search]." arXiv preprint arXiv:1701.06972 (2017).</ref>▼
* [[Adaptive website]]s{{citation needed|date=August 2017}}
* [[Affective computing]]
* [[Automated medical diagnosis]]<ref name="aima"/>▼
▲* [[Automated theorem proving]]<ref>Bridge, James P., Sean B. Holden, and Lawrence C. Paulson. "[https://www.cl.cam.ac.uk/~lp15/papers/Reports/Bridge-ml.pdf Machine learning for first-order theorem proving]." Journal of automated reasoning 53.2 (2014): 141–172.</ref><ref>Loos, Sarah, et al. "[https://arxiv.org/pdf/1701.06972 Deep Network Guided Proof Search]." arXiv preprint arXiv:1701.06972 (2017).</ref>
* [[Bioinformatics]]
* [[Brain–machine interface]]s
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* Classifying [[DNA sequence]]s
* [[Computational anatomy]]
* [[Computational linguistics]]
* [[Network simulation|Computer Networks]]
* [[Telecommunication]]▼
* [[Computer vision]], including [[object recognition]]
* [[Data quality]]<ref>{{cite journal |last1=Warncke-Wang |first1=Morten |last2=Cosley |first2=Dan |last3=Riedl |first3=John T. |title=Tell Me More: An Actionable Quality Model for Wikipedia |date=2013 |isbn=978-145031852-5 |doi=10.1145/2491055.2491063 |url=https://wikipediaquality.com/wiki/Tell_Me_More:_An_Actionable_Quality_Model_for_Wikipedia |journal=Service Business | volume = 7 | issue = 4 | year = 2013 | pages= 687--711}}</ref><ref>{{Cite journal |last1=Lewoniewski |first1=Włodzimierz |last2=Węcel |first2=Krzysztof |last3=Abramowicz |first3=Witold |date=2016-09-22 |title=Quality and Importance of Wikipedia Articles in Different Languages |url=https://www.researchgate.net/publication/308887798 |journal=Information and Software Technologies. ICIST 2016. Communications in Computer and Information Science |volume=639 |issue= |pages=613–624 |doi=10.1007/978-3-319-46254-7_50 |access-date=2019-01-12|series=Communications in Computer and Information Science |isbn=978-3-319-46253-0}}</ref>
* Detecting [[credit-card fraud]]
* [[Financial market]] analysis▼
* [[General game playing]]<ref>Finnsson, Hilmar, and Yngvi Björnsson. "[https://vvvvw.aaai.org/Papers/AAAI/2008/AAAI08-041.pdf Simulation-Based Approach to General Game Playing]." AAAI. Vol. 8. 2008.</ref>
* [[Information retrieval]]
* [[Insurance]]▼
* [[Internet fraud]] detection<ref name="alpaydin"/>
▲* [[Computational linguistics]]
* [[Machine learning control]]
* [[Machine perception]]
* [[Machine translation]]<ref>{{cite web|url=http://english.yonhapnews.co.kr/news/2017/01/10/0200000000AEN20170110009700320.html?did=2106m|title=AI-based translation to soon reach human levels: industry officials|publisher=Yonhap news agency|accessdate=4 Mar 2017}}</ref>
▲* [[Automated medical diagnosis]]<ref name="aima"/>
* [[
▲* [[Insurance]]
* [[Natural language processing]]
* [[Natural language understanding]]<ref>Sarikaya, Ruhi, Geoffrey E. Hinton, and Anoop Deoras. "[http://www.cs.utoronto.ca/~hinton/absps/ruhijournal.pdf Application of deep belief networks for natural language understanding]." IEEE/ACM Transactions on Audio, Speech and Language Processing (TASLP) 22.4 (2014): 778–784.</ref>
* [[Mathematical optimization|Optimization]] and [[metaheuristic]]▼
* [[Online advertising]]
▲* [[Mathematical optimization|Optimization]] and [[metaheuristic]]
* [[Recommender system]]s
* [[Robot locomotion]]
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* [[Software engineering]]
* [[Speech recognition|Speech]] and [[handwriting recognition]]
▲* [[Financial market]] analysis
* [[Structural health monitoring]]
* [[Syntactic pattern recognition]]
▲* [[Telecommunication]]
* [[Time series|Time series forecasting]]
* [[User behavior analytics]]{{div col end}}
▲* [[Machine translation]]<ref>{{cite web|url=http://english.yonhapnews.co.kr/news/2017/01/10/0200000000AEN20170110009700320.html?did=2106m|title=AI-based translation to soon reach human levels: industry officials|publisher=Yonhap news agency|accessdate=4 Mar 2017}}</ref>{{div col end}}
In 2006, the online movie company [[Netflix]] held the first "[[Netflix Prize]]" competition to find a program to better predict user preferences and improve the accuracy on its existing Cinematch movie recommendation algorithm by at least 10%. A joint team made up of researchers from [[AT&T Labs]]-Research in collaboration with the teams Big Chaos and Pragmatic Theory built an [[Ensemble Averaging|ensemble model]] to win the Grand Prize in 2009 for $1 million.<ref>[https://web.archive.org/web/20151110062742/http://www2.research.att.com/~volinsky/netflix/ "BelKor Home Page"] research.att.com</ref> Shortly after the prize was awarded, Netflix realized that viewers' ratings were not the best indicators of their viewing patterns ("everything is a recommendation") and they changed their recommendation engine accordingly.<ref>{{cite web|url=http://techblog.netflix.com/2012/04/netflix-recommendations-beyond-5-stars.html|title=The Netflix Tech Blog: Netflix Recommendations: Beyond the 5 stars (Part 1)|publisher=|accessdate=8 August 2015}}</ref> In 2010 The Wall Street Journal wrote about the firm Rebellion Research and their use of machine learning to predict the financial crisis.<ref>{{cite web|url=https://www.wsj.com/articles/SB10001424052748703834604575365310813948080|title=Letting the Machines Decide|author=Scott Patterson|date=13 July 2010|publisher=[[The Wall Street Journal]]|accessdate=24 June 2018}}</ref> In 2012, co-founder of [[Sun Microsystems]], [[Vinod Khosla]], predicted that 80% of medical doctors jobs would be lost in the next two decades to automated machine learning medical diagnostic software.<ref>{{cite web|url=https://techcrunch.com/2012/01/10/doctors-or-algorithms/|author=Vonod Khosla|publisher=Tech Crunch|title=Do We Need Doctors or Algorithms?|date=January 10, 2012}}</ref> In 2014, it was reported that a machine learning algorithm had been applied in the field of art history to study fine art paintings, and that it may have revealed previously unrecognized influences between artists.<ref>[https://medium.com/the-physics-arxiv-blog/when-a-machine-learning-algorithm-studied-fine-art-paintings-it-saw-things-art-historians-had-never-b8e4e7bf7d3e When A Machine Learning Algorithm Studied Fine Art Paintings, It Saw Things Art Historians Had Never Noticed], ''The Physics at [[ArXiv]] blog''</ref>
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