Eğitim İçeriği
Giriş
Data Mining Kavramlarına Genel Bakış
Data Mining Teknikleri
Birliktelik Kurallarını Bulma
Varlıkları Eşleştirme
Ağları Analiz Etme
Metnin Duygusunu Analiz Etme
Adlandırılmış Varlıkları Tanıma
Metin Özetleme Uygulama
Konu Modelleri Oluşturma
Veri Anormalliklerini Tespit Etme
En İyi Uygulamalar
Özet ve Sonuç
Kurs İçin Gerekli Önbilgiler
- Python programlama bilgisi.
- Genel olarak Python kütüphaneleri anlama.
Hedef Kitle
- Veri analistleri
- Veri bilimcileri
Danışanlarımızın Yorumları (5)
The fact of having more practical exercises using more similar data to what we use in our projects (satellite images in raster format)
Matthieu - CS Group
Eğitim - Scaling Data Analysis with Python and Dask
Very good preparation and expertise of a trainer, perfect communication in English. The course was practical (exercises + sharing examples of use cases)
Monika - Procter & Gamble Polska Sp. z o.o.
Eğitim - Developing APIs with Python and FastAPI
It was a though course as we had to cover a lot in a short time frame. Our trainer knew a lot about the subject and delivered the content to address our requirements. It was lots of content to learn but our trainer was helpful and encouraging. He answered all our questions with good detail and we feel that we learned a lot. Exercises were well prepared and tasks were tailored accordingly to our needs. I enjoyed this course
Bozena Stansfield - New College Durham
Eğitim - Build REST APIs with Python and Flask
Trainer develops training based on participant's pace
Farris Chua
Eğitim - Data Analysis in Python using Pandas and Numpy
I mostly enjoyed everything.