Apakah Anda tertarik dengan Data Science dan mencari ‘pintu gerbang’ ke bidang yang sedang ‘booming’ saat ini? Jika Ya, maka kursus Pengantar Machine Learning ini sangat cocok untuk Anda!
Machine Learning adalah seperangkat teknik yang digunakan oleh Data Scientist yang telah banyak dibicarakan dalam beberapa tahun terakhir ini. Karena aplikasinya yang sangat variatif dan menjanjikan!
Setelah Data Scientist menyelesaikan pekerjaannya mengumpulkan, membersihkan, dan menjelajahi data, maka dia dapat melanjutkan ke bagian pemodelan. Proses inilah yang akan kita pelajari bersama dalam Pengantar Machine Learning ini.
Anda akan menemukan serangkaian teknik hebat untuk membuat sebuah model prediktif (yang memiliki kemampuan belajar sendiri / self-learning) dari sebuah data set!
Saya sarankan Anda melakukannya selangkah demi selangkah, dengan tetap sedekat mungkin dengan permasalahan nyata yang dapat dipecahkan oleh Data Science.
Tujuan Kursus:
- – Mengenal Machine Learning dalam Data Science
- – Mengidentifikasi kemungkinan Machine Learning
- – Mengidentifikasi teknik dan tools pada Machine Learning
- – Latihan algoritma regresi linier
- – Mengidentifikasi keterbatasan Machine Learning
Prasyarat:
Kursus ini merupakan gabungan antara matematika dan ilmu komputer. Jika Anda tidak memiliki prasyarat di bawah ini, jangan khawatir untuk mengikuti kursus ini, karena pada kursus ini kita akan memberikan Anda gambaran yang jelas tentang ekosistem dan metode dalam dunia Data Science.
Untuk dapat memanfaatkan sepenuhnya kursus ini, kita perlu untuk menyegarkan ingatan tentang:
- – Python untuk komputasi numerik;
- – beberapa pengertian aljabar linier, seperti manipulasi vektor, perkalian matriks, norma;
- – beberapa istilah probabilitas dan statistik, seperti distribusi, probabilitas dan varians.
Tools yang diperlukan:
- – scikit-learn
- – Jupyter Notebook
Instruktur:
Abdusy Syarif telah menyelesaikan Kursus Machine Learning dari Centrale-Supéléc, Paris, France. Kini Abdusy ingin berbagi kepada teman-teman di Tanah Air Indonesia.
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