How Google does Machine Learning
Google Cloud and Google via Coursera
Overview
Class Central Tips
What is machine learning, and what kinds of problems can it solve? Google thinks about machine learning slightly differently -- of being about logic, rather than just data. We talk about why such a framing is useful for data scientists when thinking about building a pipeline of machine learning models.
Then, we discuss the five phases of converting a candidate use case to be driven by machine learning, and consider why it is important the phases not be skipped. We end with a recognition of the biases that machine learning can amplify and how to recognize this.
>>> By enrolling in this specialization you agree to the Qwiklabs Terms of Service as set out in the FAQ and located at: https://qwiklabs.com/terms_of_service
Then, we discuss the five phases of converting a candidate use case to be driven by machine learning, and consider why it is important the phases not be skipped. We end with a recognition of the biases that machine learning can amplify and how to recognize this.
>>> By enrolling in this specialization you agree to the Qwiklabs Terms of Service as set out in the FAQ and located at: https://qwiklabs.com/terms_of_service
Syllabus
- Introduction to Course
- Introduces the specialization and the Google experts who will be teaching it.
- What it means to be AI first
- In this module, you explore building a data strategy around machine learning.
- How Google does ML
- This module is about the organizational know-how Google has acquired over the years.
- Inclusive ML
- This module will discuss why machine learning systems aren’t fair by default and some of the things you have to keep in mind as you infuse ML into your products.
- Python Notebooks in the cloud
- Understand the role of AI Platform Notebooks
- Summary
- Review the core ML topics that this specialization will cover.
Taught by
Google Cloud Training
Related Courses
Reviews
4.7 rating, based on 3 reviews
-
As the course name tells us, this 1-week course introduces Machine Learning products from Google, including how Google frames an ML problem, how Google pre-trained models in the cloud, and so on.
But if you want to learn ML algorithms more deeply, this course is not suitable for you. And having a deep understanding of ML algorithms is important in the real working environment. -
Dimitrios Tosidis completed this course, spending 8 hours a week on it and found the course difficulty to be easy.
Very nice introduction to machine learning and the notebooks in the Google Cloud. I found the videos very interesting and the tests very clever. This was an extraordinary training. -
Aseem Bansal completed this course, spending 8 hours a week on it and found the course difficulty to be easy.
I already knew bit about google cloud so the parts related to that were not new for me. But the parts where they were talking ML strategy was totally new for me. Some of it like replacing rules by ML totally blew my mind. First time hearing that stuff.
Never Stop Learning!
