Eğitim İçeriği
Uygulamalı Machine Learning'e Giriş
- İstatistiksel öğrenme ve Makine öğrenmesi
- İterasyon ve değerlendirme
- Önyargı-Varyans dengesi
Machine Learning ile Python
- Kütüphane seçimi
- Ek araçlar
Regresyon
- Doğrusal regresyon
- Genellemeler ve Doğrusallık Dışı Durumlar
- Alıştırmalar
Sınıflandırma
- Bayes yenilemesi
- Naive Bayes
- Lojistik regresyon
- K-En Yakın Komşular
- Alıştırmalar
Çapraz Doğrulama ve Yeniden Örnekleme
- Çapraz doğrulama yaklaşımları
- Bootstrap
- Alıştırmalar
Unsupervised Learning
- K-ortalamalar kümeleme
- Örnekler
- Denetimsiz öğrenmenin zorlukları ve K-ortalamaların ötesi
Kurs İçin Gerekli Önbilgiler
Python programlama diline aşinalık. İstatistik ve doğrusal cebir konusunda temel bilgi sahibi olmak önerilir.
Danışanlarımızın Yorumları (5)
The trainer showed that he has a good understanding of the subject.
Marino - EQUS - The University of Queensland
Eğitim - Machine Learning with Python – 2 Days
It was a great intro to ML!! I liked the whole thing, really. The organization was perfect. The right amount of time for lectures/ demos and just us playing around. Lots of topics were touched, just at the right level. He was also very good at keeping us super engaged, even without any camera being on.
Zsolt - EQUS - The University of Queensland
Eğitim - Machine Learning with Python – 2 Days
Clarity of explanation and knowledgeable response to questions.
Harish - EQUS - The University of Queensland
Eğitim - Machine Learning with Python – 2 Days
The knowledge of the trainer was very high and the material was well prepared and organised.
Otilia - TCMT
Eğitim - Machine Learning with Python – 2 Days
I thought the trainer was very knowledgeable and answered questions with confidence to clarify understanding.