Table of contents
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1. Machine learning canvas
O tren la hinh anh ve nhung yeu to de xay dung mot san pham ML. Nhu vay o nhung hang muc chung ta can lam ro o tren thi con nhung hang muc nao khac chua duoc de cap hay khong.
- Background: Mo ta ve mong muon va nhung kho khan cua khach hang
- Value proposition: San pham cua chung ta se tao ra nhung gia tri gi va giai quyet nhung kho khan gi.
- Objectives: Mot vai muc tieu chinh ma san pham chung ta phai cung cap duoc.
- Solution: Huong giai quyet, bao gom nhung tinh nang, nhung constraints va nhung thu chung ta khong phai quan tam den.
- Feasibility: Tinh kha thi cua huong giai uyet khi ma chung ta duoc ung cap dau du resources.
- Data: Xac dinh duoc nguon du lieu duoc dung de train va trong luc production.
- Metrics: Nhung metrics nao duoc dung de danh gia cac muc tieu chinh cua san pham
- Evaluation: Sau khi xac dinh duoc metrics duoc su dung de danh gia, thi chung ta can danh gia nhu the nao?
- Modeling: Nhung phuong phap duoc dung de mo hinh hoa bai toan cua chung ta.
- Inference: Xac dinh duoc cach chung ta infer mo hinh de phu hop voi nhu cau cua nguoi dung
- Feedback: Lam sao de chung ta co the nhan duoc nhung phan hoi sau moi iteration.
- Project: Xac dinh members, deadline, roadmap, etc..
Cac yeu to minh nghi con thieu:
- Lien quan den accounting, funding cua du an.
Hay xem xet thu xem moi yeu to tren tuong duong voi vi tri nao o trong mot cong ty cong nghe:
- Background + Value Proposition + Objectives + Project: Product Manager + Customer Success Manager
- Solution: Researcher + Product Manager + Senior Engineer
- Feasibility: Product Manager giao tiep voi cac Engineer.
- Data, Metrics, evaluation: Data Scientist va ML Engineer va AI Engineer
- Modeling, Inference, Feedback: ML Engineer & AI Engineer
∞. Cau hoi
- Product Manager dong gop nhu the nao vao xay dung Solutions va Metrics.