filmov
tv
Mastering Machine Learning for Product Managers | #AskMeAnything
Показать описание
Dive into the world of Machine Learning Product Management with our insightful #AskMeAnything webinar featuring expert Product League mentors Asaf Bord, Eldad Gal, and Avi Latner. Hosted by Moriya Kassis, founder & GM of Product League, this recorded session offers valuable insights on building a successful career as a Machine Learning Product Manager.
In this webinar, you'll discover:
🟠 When and why to incorporate Machine Learning into your product strategy
🟠 How to kickstart your journey as a Machine Learning Product Manager
🟠 Strategies for building empowered research, development, and product teams
🟠 Lessons learned from developing Machine Learning-based products
🟠 Common Machine Learning mistakes to avoid
🟠 Tools to enhance your knowledge of ML, NLP, and Data Science
Among the questions our mentors answered were:
[06:13] In which cases you will recommend using Machine Learning?
[09:40] How does the development of Machine learning-based products differ from other products?
[13:45] Tell us the story of a feature, from inception to production.
[18:36] Where is the border on the technical knowledge you need to manage an ML product?
[21:31] How much are you involved in the decision on which technology to go with
[26:06] Is it you or your engineering partners that derive the decision to use Machine Learning?
[29:58] Machine Learning vs. No Machine Learning/stats learning in the product. What’s the key thing that’s different?
[31:51] How to learn the model and experiment at the very early stage, when you don't have enough users and data?
[38:49] SW development teams vs. Machine Learning/AI teams have different methodologies and flows. How to bridge those gaps and communicate those differences between the groups and especially the management? What is the role of a PM in this process?
[44:52] Tips for people with non-technical backgrounds getting started in Machine Learning?
[51:55] Can you recommend tools for Machine Learning based Product Management?
Key discussion points include:
🟠 Identifying appropriate use cases for Machine Learning in product development
🟠 Differences between ML-based product development and traditional product development
🟠 The Product Manager's role in technical decision-making for ML projects
🟠 Bridging the gap between software development and ML/AI teams
🟠 Strategies for early-stage ML model learning and experimentation
🟠 Tips for non-technical professionals entering the ML Product Management field
🟠 Recommended tools for Machine Learning-based Product Management
Whether you're new to Machine Learning or looking to refine your existing ML Product Management skills, this webinar offers practical insights to help you excel in this rapidly evolving field. Don't miss this opportunity to learn from industry experts and elevate your Product Management career!
In this webinar, you'll discover:
🟠 When and why to incorporate Machine Learning into your product strategy
🟠 How to kickstart your journey as a Machine Learning Product Manager
🟠 Strategies for building empowered research, development, and product teams
🟠 Lessons learned from developing Machine Learning-based products
🟠 Common Machine Learning mistakes to avoid
🟠 Tools to enhance your knowledge of ML, NLP, and Data Science
Among the questions our mentors answered were:
[06:13] In which cases you will recommend using Machine Learning?
[09:40] How does the development of Machine learning-based products differ from other products?
[13:45] Tell us the story of a feature, from inception to production.
[18:36] Where is the border on the technical knowledge you need to manage an ML product?
[21:31] How much are you involved in the decision on which technology to go with
[26:06] Is it you or your engineering partners that derive the decision to use Machine Learning?
[29:58] Machine Learning vs. No Machine Learning/stats learning in the product. What’s the key thing that’s different?
[31:51] How to learn the model and experiment at the very early stage, when you don't have enough users and data?
[38:49] SW development teams vs. Machine Learning/AI teams have different methodologies and flows. How to bridge those gaps and communicate those differences between the groups and especially the management? What is the role of a PM in this process?
[44:52] Tips for people with non-technical backgrounds getting started in Machine Learning?
[51:55] Can you recommend tools for Machine Learning based Product Management?
Key discussion points include:
🟠 Identifying appropriate use cases for Machine Learning in product development
🟠 Differences between ML-based product development and traditional product development
🟠 The Product Manager's role in technical decision-making for ML projects
🟠 Bridging the gap between software development and ML/AI teams
🟠 Strategies for early-stage ML model learning and experimentation
🟠 Tips for non-technical professionals entering the ML Product Management field
🟠 Recommended tools for Machine Learning-based Product Management
Whether you're new to Machine Learning or looking to refine your existing ML Product Management skills, this webinar offers practical insights to help you excel in this rapidly evolving field. Don't miss this opportunity to learn from industry experts and elevate your Product Management career!