In　recent　years,　machine　learning　has　always　been　a　research　hotspot,　and　has　been　applied　to　various　fields　with　an　important　role　played.　However,　as　the　data　amount　continues　to　increase,　the　training　time　of　machine　learning　algorithms　is　getting　longer.　Meanwhile,　quantum　computers　demonstrate　a　powerful　computing　ability.　Therefore,　researchers　try　to　solve　the　problem　of　long　machine　learning　training　time,　which　leads　to　the　emergence　of　quantum　machine　learning.　Quantum　machine　learning　algorithms　have　been　proposed,　including　quantum　principal　component　analysis,　quantum　support　vector　machine,　and　quantum　deep　learning.　Additionally,　experiments　have　proven　that　quantum　machine　learning　algorithms　have　a　significant　acceleration　effect,　leading　to　a　gradual　upward　trend　in　research　on　quantum　machine　learning.　This　study　reviews　research　on　quantum　machine　learning　algorithms.　First,　the　fundamental　concepts　of　quantum　computing　are　introduced.　Then,　five　quantum　machine　learning　algorithms　are　presented,　including　quantum　supervised　learning,　quantum　unsupervised　learning,　quantum　semi-supervised　learning,　quantum　reinforcement　learning,　and　quantum　deep　learning.　Next,　related　applications　of　quantum　machine　learning　are　demonstrated　with　the　algorithm　experiments　provided.　Finally,　the　relevant　summary　and　prospect　of　future　study　are　discussed.　©　2024　Chinese　Academy　of　Sciences.　All　rights　reserved.