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Đề cương khóa học
Giới thiệu
Tổng quan về các Khái niệm Data Mining
Data Mining Techniques
Tìm kiếm Quy tắc Liên kết
Đối sánh Thực thể
Phân tích Mạng lưới
Phân tích Cảm xúc của Văn bản
Nhận dạng Thực thể Được Gọi Tên
Triển khai Tóm tắt Văn bản
Tạo Mô hình Chủ đề
Phát hiện Dữ liệu Bất thường
Các Thực hành Tốt nhất
Tóm tắt và Kết luận
Requirements
- Sự hiểu biết về lập trình Python.
- Sự hiểu biết về các thư viện nói chung.
Đối tượng
- Chuyên viên phân tích dữ liệu
- Nhà khoa học dữ liệu
14 Hours
Testimonials (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
Course - 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.
Course - 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
Course - Build REST APIs with Python and Flask
Trainer develops training based on participant's pace
Farris Chua
Course - Data Analysis in Python using Pandas and Numpy
I mostly enjoyed everything.
