Product Management
Machine Learning for PMs
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Learn Machine Learning for PMs with the Practica AI Coach
The Practica AI Coach helps you improve in Machine Learning for PMs by using your current work challenges as opportunities to improve. The AI Coach will ask you questions, instruct you on concepts and tactics, and give you feedback as you make progress.Intro to Machine Learning for PMs
Machine Learning is a powerful tool for product managers to improve their decision-making processes. It involves the use of algorithms and statistical models to analyze data and make predictions. By understanding the basics of Machine Learning, PMs can better leverage this technology to drive business outcomes.
Machine Learning for Product Managers Part I — Problem MappingThis comprehensive 3-part article series covers: 1) Problem Mapping: What types of problems are best suited for Machine Learning 2) ML Skills: What additional skills does a PM need to build products that leverage Machine Learning? 3) Caveats: What are the common mistakes made in building products that use Machine Learning
How PMs Help Execute ML Projects
PMs play a crucial role in executing Machine Learning projects. They must work closely with data scientists, engineers, and other stakeholders to ensure that the project meets business objectives. PMs must also have a deep understanding of the technical aspects of Machine Learning to effectively communicate with their team and make informed decisions. Collaboration and communication are key to successful ML projects.
Machine Learning from a Product PerspectiveInga uses case studies from Squarespace and Automatic to show what problems are good for ML, how PMs help execute ML projects, and how to augment the standard product development lifecycle to build ML products.
No Machine Learning in Your Product? Start HereClemens covers the three different levels where ML can integrate with your product - making features better, making a new feature possible, or making a new product itself possible. He also covers an overview of tools in the ML toolbox - recommendation systems, event prediction, classification, generative models, and clustering. He wraps up with a case study on how ML is used in Google Forms.
Product Management for AIPete's presentation provides insight into how ML impacts product development and product management processes.
Related Skills
- Senior Product Manager's Role
- Group Product Manager Role
- Data Product Management
- Gamification
- Growth Product Management
- Moving Into Product Management
- Product Management Career Ladders
- Product Roadmaps
- Product Strategy
- Requirement Writing
- Product Analytics
- A/B Testing
- Problems vs. Solutions
- Customer Interviews
- Product Prioritization
- Product Vision
- Feature Kickoffs
- User Onboarding
- Product Launches
- Retrospectives
- Stakeholder Management
- Customer Development
- Working With Engineers
- Customer Delight
- Release Communication
- Hiring Product Managers
- Cross-Functional Leadership
- Finance for PMs
- Product Sense
- Outcome Orientation
- Platform Product Management
- Structuring Product Teams
- Working With Designers
- Managing Product Managers
- Feature Flags
- Working With Sales
- User Adoption
- Product Manager Seniority
- User Engagement
- PM Team Meetings
- Synthesizing Research
- PM Frameworks
- Domain Knowledge
- Onboarding Product Managers
- Product Feedback
- User Research
- Wireframing