Machine Learning: Balancing model performance with business goals
This post is designed to give some guidance for evaluating the use of machine learning to solve your business problem. As a data scientist, I am highly motivated to find the "best" model -- how close to perfect can I get my predictions to be? However, more often than not, the incremental gain I'm straining for is not necessary. The success criteria I prioritize isn't always the same quantifier the business is optimizing for. For example, if I tell you a client of mine implemented a model with 64.2% accuracy you might be appalled.
相關推薦
Machine Learning: Balancing model performance with business goals
This post is designed to give some guidance for evaluating the use of machine learning to solve your business problem. As a data scientist, I am highly mot
Artificial Intelligence and Machine Learning Require a Better Network Business Technology
All of these apps generate extreme volumes of data that must be collected and processed in real time. Networks built as recently as 10 years ago weren't re
論文翻譯：Learning Graphical Model Parameters with Ap-proximate Marginal Inference
Abstract 基於似然的圖形模型學習面臨著計算複雜度和模型錯誤描述魯棒性的限制。本文研究了直接擬合引數以最大限度地提高測量精度的方法預測的邊緣，考慮到訓練時間模型和推理方法。對成像問題的實驗表明，基於邊際化的學習在基於近似性的困難問題上比基於可能性的近似方
How to Scale Machine Learning Data From Scratch With Python
Tweet Share Share Google Plus Many machine learning algorithms expect data to be scaled consiste
Save and Load Machine Learning Models in Python with scikit
Hello Jason, I am new to machine learning. I am your big fan and read a lot of your blog and books. Thank you very much for teaching us machine le
Machine Learning Algorithms From Scratch: With Python
I believe my books offer thousands of dollars of education for tens of dollars each. They are months if not years of experience distilled into a few hundre
Metrics to measure machine learning model performance
How to read: It depends on what you want to measure. For accuracy, a value closer to 1 (or 100%) is better.Gains chartsThis metric measures how a model per
Balancing CartPole with Machine Learning
Learn how to balance a CartPole using machine learning in this article by Sean Saito, the youngest ever Machine Learning Developer at SAP and the first
[Javascript] Classify text into categories with machine learning in Natural
bus easy ann etc hms scrip steps spam not In this lesson, we will learn how to train a Naive Bayes classifier or a Logistic Regression cl
[Javascript] Classify JSON text data with machine learning in Natural
comm about cnblogs ++ get ssi learn clas save In this lesson, we will learn how to train a Naive Bayes classifier and a Logistic Regressi
學習 Machine Learning Mastery With Python （1）
測試套件 實際應用 十分 機器學習 小數 機器學習算法 很多 結果 分鐘 1 介紹 1.1 機器學習的錯誤的想法 一定要對python 編程和python語法非常了解 深入學習scikit learn使用的機器學習算法的理論和參數 避免或者不能接觸實際項目中的其他部分。
機器學習系統設計（Building Machine Learning Systems with Python）- Willi Richert Luis Pedro Coelho
切分 秘密 閾值 isa 占用 第二版 思考 並且 了解 機器學習系統設計（Building Machine Learning Systems with Python）- Willi Richert Luis Pedro Coelho 總述 本書是 2014 的，看完以後才
文獻導讀 - Machine Learning Identifies Stemness Features Associated with Oncogenic Dedifferentiation
cer 基因組 .html content web baidu ide mat 人類 參考： Machine Learning Identifies Stemness Features Associated with Oncogenic Dedifferentiation
OReilly.Hands-On.Machine.Learning.with.Scikit-Learn.and.TensorFlow學習筆記彙總
其中用到的知識點我都記錄在部落格中了：https://blog.csdn.net/dss_dssssd 第一章知識點總結： supervised learning k-Nearest Neighbors Linear Regression
Hands-on Machine Learning with Scikit-Learn and TensorFlow（中文版）和深度學習原理與TensorFlow實踐-學習筆記
監督學習：新增標籤。學習的目標是求出輸入與輸出之間的關係函式y=f(x)。樸素貝葉斯、邏輯迴歸和神經網路等都屬於監督學習的方法。 監督學習主要解決兩類核心問題，即迴歸和分類。 迴歸和分類的區別在於強調一個是連續的，一個是離散的。 非監督學習：不新增標籤。學習目標是為了探索樣本資料之間是否
Introduction to Machine Learning with Python/Python機器學習基礎教程_程式碼修改與更新
2.3.1樣本資料集 --程式碼bug及修改意見 import matplotlib.pyplot as plt import mglearn X,y=mglearn.datasets.make_forge() mglearn.discrete_scatter(X[:,0
Classification and inference with machine learning
machine learning作業代寫、代做Markdown留學生作業、代寫python, C/C++程式語言作業Project 3Classification and inference with machine learningThis notebook is arranged in cells. Te
Deploying a Machine Learning Model as a REST API
As a Python developer and data scientist, I have a desire to build web apps to showcase my work. As much as I like to design and code the front-end, i
筆記回顧2|Adversarial Machine Learning‘s Threat Model
Firstly, thank to SoK: Towards the Science of Security and Privacy in Machine Learning. 本章節主要討論下這篇文章中，在AML中的threat model。其中內容會借鑑部分參考文獻的思路
Machine Learning is Fun Part 5: Language Translation with Deep Learning and the Magic of Sequences
Making Computers TranslateSo how do we program a computer to translate human language?The simplest approach is to replace every word in a sentence with the