Deploying Machine Learning Models

本課程是 Python Data Products for Predictive Analytics 專項課程專項課程的一部分

3.6
星
44 個評分

Ilkay Altintas 另外 +1 位授課教師

提供方

Python Data Products for Predictive Analytics 專項課程加州大学圣地亚哥分校

課程信息

In this course we will learn about Recommender Systems (which we will study for the Capstone project), and also look at deployment issues for data products. By the end of this course, you should be able to implement a working recommender system (e.g. to predict ratings, or generate lists of related products), and you should understand the tools and techniques required to deploy such a working system on real-world, large-scale datasets.
This course is the final course in the Python Data Products for Predictive Analytics Specialization, building on the previous three courses (Basic Data Processing and Visualization, Design Thinking and Predictive Analytics for Data Products, and Meaningful Predictive Modeling). At each step in the specialization, you will gain hands-on experience in data manipulation and building your skills, eventually culminating in a capstone project encompassing all the concepts taught in the specialization.

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第 4 門課程（共 4 門）

Python Data Products for Predictive Analytics 專項課程

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完成時間大約為11 小時

英語（English）

字幕：阿拉伯語（Arabic）, 法語（French）, （歐洲人講的）葡萄牙語, 中文（簡體）, 意大利語, 越南語, 韓語, 德語（German）, 俄語（Russian）, 土耳其語（Turkish）, 英語（English）, 西班牙語（Spanish）

您將學到的內容有

Project structure of interactive Python data applications

Python web server frameworks: (e.g.) Flask, Django, Dash

Best practices around deploying ML models and monitoring performance

Deployment scripts, serializing models, APIs

您將獲得的技能

Python ProgrammingBig Data ProductsRecommender Systems

可分享的證書

完成後獲得證書

100% 在線

立即開始，按照自己的計劃學習。

第 4 門課程（共 4 門）

Python Data Products for Predictive Analytics 專項課程

可靈活調整截止日期

根據您的日程表重置截止日期。

完成時間大約為11 小時

英語（English）

講師

Ilkay Altintas

Chief Data Science Officer

San Diego Supercomputer Center

394,365 個學生

12 門課程

Julian McAuley

提供方

加州大学圣地亚哥分校

UC San Diego is an academic powerhouse and economic engine, recognized as one of the top 10 public universities by U.S. News and World Report. Innovation is central to who we are and what we do. Here, students learn that knowledge isn't just acquired in the classroom—life is their laboratory.

教學大綱 - 您將從這門課程中學到什麼

週

週 1

完成時間為 3 小時

Introduction

Welcome to the first week of Deploying Machine Learning Models! We will go over the syllabus, download all course materials, and get your system up and running for the course. We will also introduce the basics of recommender systems and differentiate it from other types of machine learning

完成時間為 3 小時

5 個視頻（總計 54 分鐘）, 3 個閱讀材料, 3 個測驗

5 個視頻

Introduction to Recommender Systems4分鐘

Recommender Systems versus Other Forms of Supervised Learning7分鐘

Collaborative Filtering-Based Recommendation19分鐘

Latent Factor Models (Part 1)11分鐘

Latent Factor Models (Part 2)11分鐘

3 個閱讀材料

Syllabus10分鐘

Course Materials10分鐘

Setting Up Your System10分鐘

3 個練習

Review: Recommender Systems30分鐘

Review: Introduction to Latent Factor Models30分鐘

Recommender Systems and Latent Factor Models20分鐘

週

週 2

完成時間為 1 小時

Implementing Recommender Systems

This week, we will learn how to implement a similarity-based recommender, returning predictions similar to an user's given item. We will cover how to optimize these models based on gradient descent and Jaccard similarity.

完成時間為 1 小時

4 個視頻（總計 36 分鐘）

週

週 3

完成時間為 1 小時

Deploying Recommender Systems

This week, we will learn about Python web server frameworks and the overall structure of interactive Python data applications. We will also cover some tips for best practices on deploying and monitoring your applications.

完成時間為 1 小時

3 個視頻（總計 17 分鐘）, 1 個閱讀材料, 2 個測驗

週

週 4

完成時間為 2 小時

Project 4: Recommender System

For this final project, you will build a recommender system of your own. Find a dataset, clean it, and create a predictive system from the dataset. This will help prepare you for the upcoming capstone, where you will harness your skills from all courses of this specialization into one single project!

完成時間為 2 小時

2 個閱讀材料

審閱

3.6

14 條評論

5 stars
36.36%
4 stars
25%
3 stars
13.63%
2 stars
9.09%
1 star
15.90%

來自DEPLOYING MACHINE LEARNING MODELS的熱門評論

由 ML 提供2020年12月6日

I Liked the Course in general especially the recommender component. I would seriously recommend making major improvements and clarification to the capstone project.

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關於 Python Data Products for Predictive Analytics 專項課程

Python data products are powering the AI revolution. Top companies like Google, Facebook, and Netflix use predictive analytics to improve the products and services we use every day. Take your Python skills to the next level and learn to make accurate predictions with data-driven systems and deploy machine learning models with this four-course Specialization from UC San Diego.

This Specialization is for learners who are proficient with the basics of Python. You’ll start by creating your first data strategy. You’ll also develop statistical models, devise data-driven workflows, and learn to make meaningful predictions for a wide-range of business and research purposes. Finally, you’ll use design thinking methodology and data science techniques to extract insights from a wide range of data sources. This is your chance to master one of the technology industry’s most in-demand skills. Python Data Products for Predictive Analytics is taught by Professor Ilkay Altintas, Ph.D. and Julian McAuley. Dr. Alintas is a prominent figure in the data science community and the designer of the highly-popular Big Data Specialization on Coursera. She has helped educate hundreds of thousands of learners on how to unlock value from massive datasets.

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Deploying Machine Learning Models