[Đánh giá] Machine Learning Pocket Reference (Matt Harrison) Tóm tắt.

Machine Learning Pocket Reference (Matt Harrison) - Amazon USA Store: https://www.amazon.com/dp/1492047546?tag=9natree-20 - Amazon Worldwide Store: https://global.buys.trade/Machine-Learning-Pocket-Reference-Matt-Harrison.html - Apple Books: https://books.apple.com/us/audiobook/linux-the-quick-start-beginners-guide-unabridged/id1164191831?itsct=books_box_link&itscg=30200&ls=1&at=1001l3bAw&ct=9natree - eBay: https://www.ebay.com/sch/i.html?_nkw=Machine+Learning+Pocket+Reference+Matt+Harrison+&mkcid=1&mkrid=711-53200-19255-0&siteid=0&campid=5339060787&customid=9natree&toolid=10001&mkevt=1 - Shopee: https://asia.buys.trade/shopee_Machine-Learning-Pocket-Reference-Matt-Harrison.html - Lazada: https://asia.buys.trade/lazada_Machine-Learning-Pocket-Reference-Matt-Harrison.html - Tiktok: https://asia.buys.trade/tiktok_Machine-Learning-Pocket-Reference-Matt-Harrison.html - Đọc thêm: https://vietnam.9natree.com/read/1492047546/ #PhânloạivớidữliệuTitanic #Xửlýdữliệuthiếu #Chọnđặctrưng #Đánhgiáhồiquy #Pipelinescikitlearn #MachineLearningPocketReference Machine Learning Pocket Reference: Working with Structured Data in Python của Matt Harrison là sách tham khảo thực hành về học máy trên dữ liệu có cấu trúc, xuất bản bởi O’Reilly. Thay vì dạy lập trình Python từ đầu hay thay thế một khóa học đầy đủ, sách cô đọng quy trình xây dựng mô hình thành các ghi chú, bảng tóm tắt và ví dụ mã nguồn có thể tra cứu khi làm việc. Trọng tâm là dữ liệu dạng bảng, loại dữ liệu phổ biến trong phân tích kinh doanh, vận hành và nhiều bài toán dự báo thực tế. Harrison đi từ phân loại, làm sạch dữ liệu, khám phá dữ liệu, tiền xử lý và chọn đặc trưng, đến đánh giá mô hình, hồi quy, phân cụm, giảm chiều và pipeline của scikit-learn. Ví dụ phân loại dùng dữ liệu Titanic giúp nối các khái niệm với thao tác cụ thể trong Python. Cuốn sách hướng đến lập trình viên, nhà khoa học dữ liệu và kỹ sư AI đã có nền tảng Python, đặc biệt là pandas, đồng thời cần một tài liệu ngắn gọn để tổ chức và kiểm tra quy trình học máy có giám sát lẫn không giám sát.

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