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Course Outline
Pengantar Machine Learning dan Google Colab
- Ikhtisar pembelajaran mesin
- Menyiapkan Google Colab
- Python penyegaran
Pembelajaran yang Diawasi dengan Scikit-learn
- Model regresi
- Model klasifikasi
- Evaluasi dan optimasi model
Teknik Pembelajaran Tanpa Pengawasan
- Algoritma pengelompokan
- Pengurangan dimensi
- Pembelajaran aturan asosiasi
Lanjutan Machine Learning Konsep
- Jaringan saraf dan pembelajaran mendalam
- Mendukung mesin vektor
- Metode ansambel
Topik Khusus di Machine Learning
- Rekayasa fitur
- Penyetelan hiperparameter
- Interpretabilitas model
Machine Learning Alur Kerja Proyek
- Pemrosesan awal data
- Pemilihan model
- Penerapan model
Proyek Batu Penjuru
- Mendefinisikan pernyataan masalah
- Pengumpulan dan pembersihan data
- Pelatihan dan evaluasi model
Ringkasan dan Langkah Selanjutnya
Requirements
- Pemahaman tentang konsep dasar pemrograman
- Pengalaman dengan pemrograman Python.
- Familiar dengan konsep dasar statistika
Hadirin
- Ilmuwan data
- Pengembang perangkat lunak
14 Hours
Testimonials (2)
the ML ecosystem not only MLFlow but Optuna, hyperops, docker , docker-compose
Guillaume GAUTIER - OLEA MEDICAL
Course - MLflow
I enjoyed participating in the Kubeflow training, which was held remotely. This training allowed me to consolidate my knowledge for AWS services, K8s, all the devOps tools around Kubeflow which are the necessary bases to properly tackle the subject. I wanted to thank Malawski Marcin for his patience and professionalism for training and advice on best practices. Malawski approaches the subject from different angles, different deployment tools Ansible, EKS kubectl, Terraform. Now I am definitely convinced that I am going into the right field of application.
