ProductizeML
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ProductizeML
Introduction
Objectives
About the Course
Guidelines
Syllabus
After Completion
Machine Learning
Why ML, and why now
Supervised Learning
Unsupervised Learning
Deep Learning
ML Terminology
Data Management
Data Access
Data Collection
Data Curation
Train and Evaluate
Framework and Hardware
Training Neural Networks
Model Evaluation
Productize It
ML Life Cycle
Business Objectives
Data Preparation
Model Development
Train, Evaluate, and Deploy
A/B Testing
KPI Evaluation
PM Terminology
Resources
Readings
Courses
Videos
Hands-On
Python for Machine Learning
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About the Course
In order to achieve that, this course is online and open-ended regarding the product and technical delivery recommendations. The shared content will get updated periodically in order to guarantee new and state-of-the-art information.
This course is unique in its kind on account of the format the content is presented and tools provided. While video lectures can offer a really close connection between the instructor and the learner, we found that offering our course content in a written format, we are enabling anyone taking the course to find the right content instantly by using the search bar. Also, this way the content is easier to maintain and expand over time.
We expect the course community to play a really important role by engaging in the form of chats and comments of each lecture, promoting a shared course built also from every learner.
The estimated course time is 8-10 hours, including course-specific content, recommended readings from other sources like articles and blog posts, and finally a course-specific hands-on experience (coming soon!).
Once again, Welcome to this exciting course!
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Guidelines
Last modified 1yr ago
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