Deploying Machine Learning Models

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 m

( 9 Reviews )

Created by: Ilkay Altintas

Quality Score

Content Quality

Video Quality

Qualified Instructor

Course Pace

Course Depth & Coverage

Overall Score : 54 / 100

Live Chat with CourseDuck's Co-Founder for Help

Need help deciding on a artificial intelligence course? Or looking for more detail on Ilkay Altintas's Deploying Machine Learning Models? Feel free to chat below.

Join CourseDuck's Online Learning Discord Community

Course Description

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.

Time: 12h

Instructor Details

Ilkay Altintas

2.7 Rating
9 Reviews

Ilkay Altintas is the Chief Data Science Officer at the San Diego Supercomputer Center (SDSC), UC San Diego, where she is also the Founder and Director for the Workflows for Data Science Center of Excellence. Since joining SDSC in 2001, she has in the areas of computational data science and e-Sciences at the intersection of scientific workflows, provenance, distributed computing, bioinformatics, observatory systems, conceptual data querying, and software modeling. She is a co-initiator of and an active contributor to the popular open-source Kepler Scientific Workflow System. Ilkay Altintas received her Ph.D. degree from the University of Amsterdam in the Netherlands.