Teknologi machine learning (Ml) adalah mesin yang dikembangkan untuk dapat belajar dengan sendirinya tanpa arahan  dari penggunanya. Pembelajaran mesin dikembangkan berdasarkan disiplin pengetahuan lainnya.

Seperti statistika, matematika dan information mining agar mesin bisa belajar dengan menganalisa information tanpa mesti di program kembali atau diperintah. di dalam hal ini machine learning miliki kemampuan untuk memperoleh informasi yang ada denga perintah ia sendiri.

Apa itu Machine Learning?

ML juga bisa mempelajari informasi yang ada dan informasi yang ia peroleh supaya dapat menjalankan tugas khusus. Tugas yang bisa dikerjakan oleh ML pun benar-benar bermacam, tergantung  dari apa yang ia pelajari.

Istilah machine learning pertama kali dikemukakan oleh lebih dari satu ilmuwan matematika seperti Adrien Marie Legendre, Thomas Bayes dan Andrey Markov pada tahun 1920-An  dengan mengemukakan dasar-dasar machine learning dan konsepnya.

Semenjak waktu tersebut ML banyak yang mengembangkan. Salah satu contoh dari penerapan ML yang sangat terkenal adalah Deep Blue yang dibuat oleh IBM pada tahun 1996. Peran machine learning banyak menolong manusia di dalam banyak bidang.

Apalagi saat ini penerapan ML bisa dengan mudah anda temukan didalam kehidupan sehari-hari. Misalnya saat anda menggunakan fitur face unlock untuk terhubung perangkat smartphone anda, atau waktu anda menjelajah di internet atau media sosial anda akan kerap disuguhkan dengan lebih dari satu iklan. 

Cara Kerja Machine Learning

cara kerja machine learning sebenarnya berbeda-beda disesuaikan dengan teknik atau metode pembelajaran seperti apa yang anda gunakan terhadap Ml. Tapi pada dasarnya prinsip cara kerja pembelajaran mesin masih sama.

Meliputi pengumpulan informasi, eksplorasi informasi, pemilihan jenis atau teknik, memberi tambahan pelatihan pada gaya yang dipilih dan mengevaluasi hasil  dari Ml. Untuk tahu cara kerja  dari Ml, akan kami ulas cara kerja  dari sebagian penerapannya berikut ini.

Alphago merupakan machine learning yang dikembangkan oleh Google. Waktu awal dikembangkan Alphago akan dilatih dengan memberi tambahan 100 ribu informasi pertandingan Go untuk ia pelajari.

Sesudah Alphago memiliki bekal dan ilmu cara dan taktik bermain game Go  dari mempelajari 100 ribu informasi pertandingan Go itu. pemugaran cara bermain Alphago dikerjakan oleh dirinya sendiri berdasarkan pengalamannya saat ia bermain melawan dirinya sendiri atau melawan orang lain.

Alphago juga bisa mensimulasikan lebih dari satu pertandingan pada satu waktu secara sejalan. Artinya didalam satu waktu ia dapat laksanakan lebih dari satu pertandingan Go sekaligus untuk dipelajari.

Supaya proses belajar dan pengalamannya,  bermain Go juga bisa lebih banyak dibanding manusia. Hal ini terbukti ketika Alphago bermain  dengan kampiun global Go pada tahun 2016 dan ia bisa jadi pemenangnya.

Dari penerapan machine learning pada Alphago, kita dapat tahu bahwa machine learning akan tetap belajar selama ia digunakan. Serupa halnya dengan fitur deteksi wajah di foto yang dimiliki Facebook.

Ia akan belajar mengenal pola wajah anda berdasarkan tanda yang anda masukkan saat memposting suatu foto. Jadi tidak heran apabila machine learning kerap digunakan, maka taraf akurasinya semakin baik dibanding di awal-awal.  Hal ini karena machine learning sudah banyak belajar  dari pemanfaatan machine learning oleh pengguna. 

itulah sedikit penjelasan mengenai machine learning. Info ini ditulis untuk memberi ilmu dasar yang sewaktu-waktu dibutuhkan oleh mahasiswa atau siswa yang ingin belajar. Semoga membantu!

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