課程信息

100% 在線

立即開始,按照自己的計劃學習。

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13 小時

建議:9 hours/week...

英語(English)

字幕:英語(English)

您將學到的內容有

  • Check

    Project structure of interactive Python data applications

  • Check

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

  • Check

    Best practices around deploying ML models and monitoring performance

  • Check

    Deployment scripts, serializing models, APIs

您將獲得的技能

Python ProgrammingBig Data ProductsRecommender Systems

100% 在線

立即開始,按照自己的計劃學習。

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13 小時

建議:9 hours/week...

英語(English)

字幕:英語(English)

教學大綱 - 您將從這門課程中學到什麼

1
完成時間為 1 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...
2 個閱讀材料, 3 個測驗
2 個閱讀材料
Syllabus10分鐘
Setting Up Your System10分鐘
3 個練習
Review: Recommender Systems4分鐘
Review: Introduction to Latent Factor Models4分鐘
Recommender Systems and Latent Factor Models10分鐘
2
完成時間為 19 分鐘

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....
3 個測驗
3 個練習
Review: Similarity-Based Recommenders5分鐘
Review: Implementing Latent Factor Models4分鐘
Implementing Recommender Systems10分鐘
3
完成時間為 5 分鐘

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....
1 個測驗
1 個練習
Deploying Recommender Systems5分鐘
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!...
2 個閱讀材料, 1 個測驗
2 個閱讀材料
Project Description10分鐘
How to Find a Dataset10分鐘

講師

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Ilkay Altintas

Chief Data Science Officer
San Diego Supercomputer Center
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Julian McAuley

Assistant Professor
Computer Science

關於 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....

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 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....
Python Data Products for Predictive Analytics

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