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Managing Your Machine Learning Portfolio

The document discusses the management of machine learning portfolios, highlighting challenges such as misplaced modeling, crude tools, and under-supported teams. It outlines a framework for the machine learning product lifecycle, emphasizing the progression from global to local models and the importance of strategic investments in shared tooling. Additionally, it addresses necessary skills for team members and various structures for effective team collaboration.

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Managing Your Machine Learning Portfolio David Murgatroyd ( @dmurga) MassTLC ML Dev Day September 4, 2018 (please don’t sue me for copyright violation, Touchstone)
Your customer
Your customer Your ML portfolio
Your product Your customer
Credit: Marta Mandile, DensityDesign Research Lab. CC BY-SA 4.0 Your product Your customer
Your product Your customers
Your product Your customer
Your product Your customer
Your product Your customer
@dmurgaPeople by ProSymbols from the Noun Project Music by Iconnic from the Noun Project
@dmurgaPeople by ProSymbols from the Noun Project Music by Iconnic from the Noun Project
@dmurgaPeople by ProSymbols from the Noun Project Music by Iconnic from the Noun Project
@dmurgaPeople by ProSymbols from the Noun Project Music by Iconnic from the Noun Project
@dmurgaPeople by ProSymbols from the Noun Project Music by Iconnic from the Noun Project
@dmurgaPeople by ProSymbols from the Noun Project Music by Iconnic from the Noun Project
Challenges for ML Portfolios 1. Misplaced modelling. 2. Crude tools. 3. Under-supported people.
A Framework for the ML Product Lifecycle
@dmurga Research Discovery Fundamental Delivery Applied Kinds of R&D Work Development Sure it’s possible? Sureit’svaluable?
@dmurga Research Discovery Fundamental Delivery Applied Kinds of R&D Work Development Unknown to World Known to World Sure it’s possible? Known to Our Organization Sureit’svaluable?
@dmurga Research Discovery Fundamental Delivery Applied Kinds of R&D Work Development Experimental Hypothesized Unknown Known Sureit’svaluable? Unknown to World Known to World Sure it’s possible? Known to Our Organization
@dmurga Research Discovery Fundamental Delivery Applied Kinds of R&D Work: Examples Development Experimental Hypothesized Unknown Known Sureit’svaluable? Unknown to World Known to World Sure it’s possible? Known to Our Organization
@dmurga Research Discovery Fundamental Delivery Applied Kinds of R&D Work: Examples Development Experimental Hypothesized Unknown Known Sureit’svaluable? Unknown to World Known to World Sure it’s possible? Known to Our Organization
@dmurga Research Discovery Fundamental Delivery Applied Kinds of R&D Work: Examples Development Experimental Hypothesized Unknown Known Sureit’svaluable? Unknown to World Known to World Sure it’s possible? Known to Our Organization
@dmurga Research Discovery Fundamental Delivery Applied Kinds of R&D Work: Examples Development Experimental Hypothesized Unknown Known Sureit’svaluable? Unknown to World Known to World Sure it’s possible? Known to Our Organization
@dmurga Research Discovery Fundamental Delivery Applied Kinds of R&D Work: Examples Development Experimental Hypothesized Unknown Known Sureit’svaluable? Unknown to World Known to World Sure it’s possible? Known to Our Organization
@dmurga Research Discovery Fundamental Delivery Applied Kinds of R&D Work: Examples Development Experimental Hypothesized Unknown Known Sureit’svaluable? Unknown to World Known to World Sure it’s possible? Known to Our Organization
@dmurga Research Discovery Fundamental Delivery Applied Kinds of R&D Work: Examples Development Experimental Hypothesized Unknown Known Sureit’svaluable? Unknown to World Known to World Sure it’s possible? Known to Our Organization
@dmurga Research Discovery Fundamental Delivery Applied ML Product Lifecycle Development Experimental Hypothesized Unknown Known Sureit’svaluable? Unknown to World Known to World Sure it’s possible? Known to Our Organization
@dmurga Research Discovery Fundamental Delivery Applied ML Product Lifecycle Development Experimental Hypothesized Unknown Known Sureit’svaluable? Unknown to World Known to World Sure it’s possible? Known to Our Organization No New ML
@dmurga Research Discovery Fundamental Delivery Applied ML Product Lifecycle Development Experimental Hypothesized Unknown Known Sureit’svaluable? Unknown to World Known to World Sure it’s possible? Known to Our Organization No New ML Proto ML Product
@dmurga Research Discovery Fundamental Delivery Applied ML Product Lifecycle Development Experimental Hypothesized Unknown Known Sureit’svaluable? Unknown to World Known to World Sure it’s possible? Known to Our Organization No New ML Proto ML Product M.V. ML Product
@dmurga Research Discovery Fundamental Delivery Applied ML Product Lifecycle Development Experimental Hypothesized Unknown Known Sureit’svaluable? Unknown to World Known to World Sure it’s possible? Known to Our Organization Mature ML Product No New ML Proto ML Product M.V. ML Product
@dmurga Research Discovery Fundamental Delivery Applied ML Product Lifecycle Development Experimental Hypothesized Unknown Known Sureit’svaluable? Unknown to World Known to World Sure it’s possible? Known to Our Organization Mature ML Product v2 and beyond No New ML Proto ML Product M.V. ML Product
@dmurga Research Delivery Applied Alternative ML Product Lifecycle Development Experimental Hypothesized Unknown Known Sureit’svaluable? Unknown to World Known to World Sure it’s possible? Known to Our Organization Mature ML Product Proto ML Product Academic Results M.V. ML Product Industrial Lab Results Discovery Fundamental
@dmurga Research Discovery Fundamental Delivery Applied Preferred ML Product Lifecycle Development Experimental Hypothesized Unknown Known Sureit’svaluable? Unknown to World Known to World Sure it’s possible? Known to Our Organization Mature ML Product v2 and beyond No New ML Proto ML Product M.V. ML Product
Challenges for ML Portfolios 1. Misplaced modelling.
@dmurgaPeople by ProSymbols from the Noun Project Music by Iconnic from the Noun Project
@dmurgaPeople by ProSymbols from the Noun Project Music by Iconnic from the Noun Project
@dmurgaPeople by ProSymbols from the Noun Project Music by Iconnic from the Noun Project
@dmurgaPeople by ProSymbols from the Noun Project Music by Iconnic from the Noun Project
@dmurgaPeople by ProSymbols from the Noun Project Music by Iconnic from the Noun Project
@dmurgaPeople by ProSymbols from the Noun Project Music by Iconnic from the Noun Project
@dmurgaPeople by ProSymbols from the Noun Project World by Guilherme Furtado from the Noun Project
@dmurgaPeople by ProSymbols from the Noun Project World by Guilherme Furtado from the Noun Project
@dmurgaPeople by ProSymbols from the Noun Project World by Guilherme Furtado from the Noun Project
@dmurgaPeople by ProSymbols from the Noun Project World by Guilherme Furtado from the Noun Project
@dmurgaPeople by ProSymbols from the Noun Project World by Guilherme Furtado from the Noun Project Global: More data which changes relatively slowly. Local: Less data which changes relatively quickly.
@dmurgaPeople by ProSymbols from the Noun Project World by Guilherme Furtado from the Noun Project Local Models Global Models
@dmurgaPeople by ProSymbols from the Noun Project World by Guilherme Furtado from the Noun Project Global Models Local Models
@dmurgaPeople by ProSymbols from the Noun Project World by Guilherme Furtado from the Noun Project M.V. ML Product No New ML Proto ML Product Mature ML Product v2 and beyond More Global More Local ML Product Lifecycle ModelCombination
@dmurgaPeople by ProSymbols from the Noun Project World by Guilherme Furtado from the Noun Project M.V. ML Product No New ML Proto ML Product Mature ML Product v2 and beyond Progress from more global to more local models. ML Product Lifecycle More Global More Local ModelCombination
@dmurgaPeople by ProSymbols from the Noun Project World by Guilherme Furtado from the Noun Project M.V. ML Product No New ML Proto ML Product Mature ML Product v2 and beyond Progress from more global to more local models. ML Product Lifecycle More Global More Local ModelCombination
@dmurgaPeople by ProSymbols from the Noun Project World by Guilherme Furtado from the Noun Project M.V. ML Product No New ML Proto ML Product Mature ML Product v2 and beyond Progress from more global to more local models. ML Product Lifecycle More Global More Local ModelCombination
@dmurgaPeople by ProSymbols from the Noun Project World by Guilherme Furtado from the Noun Project M.V. ML Product No New ML Proto ML Product Mature ML Product v2 and beyond Progress from more global to more local models. ML Product Lifecycle More Global More Local ModelCombination
@dmurgaPeople by ProSymbols from the Noun Project World by Guilherme Furtado from the Noun Project M.V. ML Product No New ML Proto ML Product Mature ML Product v2 and beyond Progress from more global to more local models. ML Product Lifecycle More Global More Local ModelCombination
Suggestions for ML Portfolios 1. Progress from global to local models.
Challenges for ML Portfolios 1. Misplaced modelling. 2. Crude tools.
@dmurgaPeople by ProSymbols from the Noun Project Music by Iconnic from the Noun Project
@dmurgaPeople by ProSymbols from the Noun Project Music by Iconnic from the Noun Project
@dmurgaPeople by ProSymbols from the Noun Project Music by Iconnic from the Noun Project
Stages of ML Workflow Offline Evaluation Feature Trans- formation Modeling Model Serving Online Evaluation Data Pre- processing Data set Validation Where to get your ML Tools?
Stages of ML Workflow Offline Evaluation Feature Trans- formation Modeling Model Serving Online Evaluation Data Pre- processing Data set Validation Where to get your ML Tools?
Stages of ML Workflow Offline Evaluation Feature Trans- formation Modeling Model Serving Online Evaluation Data Pre- processing Data set Validation Third Party Open Source or Vendor Your Team Your Organ- ization Where to get your ML Tools?
Stages of ML Workflow Offline Evaluation Feature Trans- formation Modeling Model Serving Online Evaluation Data Pre- processing Data set Validation Third Party Open Source or Vendor Your Team Your Organ- ization Where to get your ML Tools?
Stages of ML Workflow Offline Evaluation Feature Trans- formation Modeling Model Serving Online Evaluation Data Pre- processing Data set Validation Third Party Open Source or Vendor Your Team Your Organ- ization Where to get your ML Tools?
Stages of ML Workflow Offline Evaluation Feature Trans- formation Modeling Model Serving Online Evaluation Data Pre- processing Data set Validation Third Party Open Source or Vendor Your Team Your Organ- ization Where to get your ML Tools?
Stages of ML Workflow Offline Evaluation Feature Trans- formation Modeling Model Serving Online Evaluation Data Pre- processing Data set Validation Third Party Open Source or Vendor Your Team Your Organ- ization Share starting here Where to get your ML Tools?
Stages of ML Workflow Offline Evaluation Feature Trans- formation Modeling Model Serving Online Evaluation Data Pre- processing Data set Validation Third Party Open Source or Vendor Your Team Your Organ- ization Share starting here Then here Where to get your ML Tools?
Stages of ML Workflow Offline Evaluation Feature Trans- formation Modeling Model Serving Online Evaluation Data Pre- processing Data set Validation Third Party Open Source or Vendor Your Team Your Organ- ization Where to get your ML Tools? No New ML
Stages of ML Workflow Offline Evaluation Feature Trans- formation Modeling Model Serving Online Evaluation Data Pre- processing Data set Validation Third Party Open Source or Vendor Your Team Your Organ- ization Where to get your ML Tools? No New ML Proto ML Product
Stages of ML Workflow Offline Evaluation Feature Trans- formation Modeling Model Serving Online Evaluation Data Pre- processing Data set Validation Third Party Open Source or Vendor Your Team Your Organ- ization Where to get your ML Tools? M.V. ML Product No New ML Proto ML Product
Stages of ML Workflow Offline Evaluation Feature Trans- formation Modeling Model Serving Online Evaluation Data Pre- processing Data set Validation Third Party Open Source or Vendor Your Team Your Organ- ization Where to get your ML Tools? M.V. ML Product No New ML Proto ML Product Mature ML Product
Stages of ML Workflow Offline Evaluation Feature Trans- formation Modeling Model Serving Online Evaluation Data Pre- processing Data set Validation Third Party Open Source or Vendor Your Team Your Organ- ization Where to get your ML Tools? M.V. ML Product No New ML Proto ML Product Mature ML Product v2 and beyond
Suggestions for ML Portfolios 1. Progress from global to local models. 2. Strategically invest in shared tooling.
Challenges for ML Portfolios 1. Misplaced modelling. 2. Crude tools. 3. Under-supported people.
@dmurgaPeople by ProSymbols from the Noun Project Music by Iconnic from the Noun Project
@dmurgaPeople by ProSymbols from the Noun Project Music by Iconnic from the Noun Project
@dmurgaPeople by ProSymbols from the Noun Project Music by Iconnic from the Noun Project
@dmurgaPeople by ProSymbols from the Noun Project Music by Iconnic from the Noun Project
@dmurgaPeople by ProSymbols from the Noun Project Music by Iconnic from the Noun Project Two kinds of support: 1. Individual’s Skills 2. Team Structure
@dmurga M.V. ML Product No New ML Proto ML Product Mature ML Product v2 and beyond Drive ML (State-of-the-Art) Drive ML Inform ML Understand ML Skills Needed
@dmurga M.V. ML Product No New ML Proto ML Product Mature ML Product v2 and beyond Drive ML (State-of-the-Art) Drive ML Inform ML Understand ML Designer or User Researcher Other Engineers Data Scientist ML Engineer Product Manager Skills Needed
@dmurga M.V. ML Product No New ML Proto ML Product Mature ML Product v2 and beyond Drive ML (State-of-the-Art) Drive ML Inform ML Understand ML Designer or User Researcher Other Engineers Data Scientist ML Engineer Product Manager Skills Needed
@dmurga M.V. ML Product No New ML Proto ML Product Mature ML Product v2 and beyond Drive ML (State-of-the-Art) Drive ML Inform ML Understand ML Designer or User Researcher Other Engineers Data Scientist ML Engineer Product Manager Skills Needed
@dmurga M.V. ML Product No New ML Proto ML Product Mature ML Product v2 and beyond Drive ML (State-of-the-Art) Drive ML Inform ML Understand ML Designer or User Researcher Other Engineers Data Scientist ML Engineer Product Manager Skills Needed
@dmurga M.V. ML Product No New ML Proto ML Product Mature ML Product v2 and beyond Drive ML (State-of-the-Art) Drive ML Inform ML Understand ML Designer or User Researcher Other Engineers Data Scientist ML Engineer Product Manager Skills Needed
@dmurga M.V. ML Product No New ML Proto ML Product Mature ML Product v2 and beyond Drive ML (State-of-the-Art) Drive ML Inform ML Understand ML ML EngineerSkills Needed
@dmurga Roles
@dmurga Roles
@dmurga Roles ‣ Applied ML Eng ‣ ML Tool Eng ‣ Core Researcher
@dmurga Roles ‣ Applied ML Eng ‣ Product ‣ Domain (logs, text, recs,...) ‣ Experiments ‣ Systems (BE, DE) ‣ Algorithms ‣ ML Tool Eng ‣ Core Researcher
@dmurga Roles ‣ Applied ML Eng ‣ Product ‣ Domain (logs, text, recs,...) ‣ Experiments ‣ Systems (BE, DE) ‣ Algorithms ‣ ML Tool Eng ‣ Infrastructure ‣ Algorithms ‣ Core Researcher
@dmurga Roles # Needed‣ Applied ML Eng ‣ Product ‣ Domain ‣ Experiments ‣ Systems ‣ Algorithms ‣ ML Tool Eng ‣ Infrastructure ‣ Algorithms ‣ Core Researcher
@dmurga M.V. ML Product No New ML Proto ML Product Mature ML Product v2 and beyond Drive ML (State-of-the-Art) Drive ML Inform ML Understand ML Applied ML Engineer ML Tools Engineer Skills Needed
@dmurga M.V. ML Product No New ML Proto ML Product Mature ML Product v2 and beyond Drive ML (State-of-the-Art) Drive ML Inform ML Understand ML Applied ML Engineer ML Tools Engineer Core ML Researcher Skills Needed
@dmurga M.V. ML Product No New ML Proto ML Product Mature ML Product v2 and beyond Integrated Isolated MLv.non-MLwork Team Structure
@dmurga M.V. ML Product No New ML Proto ML Product Mature ML Product v2 and beyond Integrated Isolated Central ML Squad ‣ More collaboration among MLers ‣ Harder to be product-aligned ‣ Possible deliverables: Models Systems Development effort MLv.non-MLwork Team Structure
@dmurga M.V. ML Product No New ML Proto ML Product Mature ML Product v2 and beyond Integrated Isolated Central ML Squad Cross-functional Squad ‣ Less collaboration among MLers, so need to be senior ‣ Easier to be product-aligned ‣ MLers likely to do non-ML They need to be flexible PM needs to be skilled to cross-prioritize MLv.non-MLwork
@dmurga M.V. ML Product No New ML Proto ML Product Mature ML Product v2 and beyond Integrated Isolated Central ML Squad Cross-functional Squad Separate ML Workstream ‣ Allows more focus when ML progress is more valuable ‣ Prioritization is higher-level: across streams, not tasks ‣ Lots of variety in structure and sharing MLv.non-MLwork
@dmurga M.V. ML Product No New ML Proto ML Product Mature ML Product v2 and beyond Integrated Isolated Central ML Squad Cross-functional Squad Separate ML Workstream Sibling Squad ‣ Even more focus for “step change” ‣ Need structure for alignment between siblings (eg., for online experimentation) ‣ Rare state since product discovery may be more valuable MLv.non-MLwork
@dmurga M.V. ML Product No New ML Proto ML Product Mature ML Product v2 and beyond Integrated Isolated Central ML Squad Cross-functional Squad Separate ML Workstream Sibling Squad MLv.non-MLwork
Challenges for ML Portfolios 1. Misplaced modelling. 2. Crude tools. 3. Under-supported people.
Suggestions for ML Portfolios 1. Progress from global to local models. 2. Strategically invest in shared tooling. 3. Equip individuals and their teams.
@dmurga Research Discovery Fundamental Delivery Applied Preferred ML Product Lifecycle Development Experimental Hypothesized Unknown Known Sureit’svaluable? Unknown to World Known to World Sure it’s possible? Known to Our Organization Mature ML Product v2 and beyond No New ML Proto ML Product M.V. ML Product
@dmurgaPeople by ProSymbols from the Noun Project World by Guilherme Furtado from the Noun Project M.V. ML Product No New ML Proto ML Product Mature ML Product v2 and beyond Progress from more global to more local models. ML Product Lifecycle More Global More Local ModelCombination
Stages of ML Workflow Offline Evaluation Feature Trans- formation Modeling Model Serving Online Evaluation Data Pre- processing Data set Validation Third Party Open Source or Vendor Your Team Your Organ- ization Where to get your ML Tools?
@dmurga M.V. ML Product No New ML Proto ML Product Mature ML Product v2 and beyond Drive ML (State-of-the-Art) Drive ML Inform ML Understand ML Designer or User Researcher Other Engineers Data Scientist ML Engineer Product Manager
@dmurga M.V. ML Product No New ML Proto ML Product Mature ML Product v2 and beyond Integrated Isolated Central ML Squad Cross-functional Squad Separate ML Workstream Sibling Squad MLv.non-MLwork
@dmurga
Thanks! Questions? David Murgatroyd (@dmurga) Suggestions: What kinds of ways can global and local models combine? What relation does org size have to tool source? How do you train Product Mgrs, Designers, etc., for ML product development? How does the ethics of ML Product Development fit? I hear you’re up for MassTLC’s ML in Action Award? What kind of ML roles are you hiring for in Boston? Hiring in Boston, NYC, London, and Stockholm!

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Managing Your Machine Learning Portfolio

  • 1.
    Managing Your Machine LearningPortfolio David Murgatroyd ( @dmurga) MassTLC ML Dev Day September 4, 2018 (please don’t sue me for copyright violation, Touchstone)
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    Credit: Marta Mandile,DensityDesign Research Lab. CC BY-SA 4.0 Your product Your customer
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    @dmurgaPeople by ProSymbolsfrom the Noun Project Music by Iconnic from the Noun Project
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    @dmurgaPeople by ProSymbolsfrom the Noun Project Music by Iconnic from the Noun Project
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    @dmurgaPeople by ProSymbolsfrom the Noun Project Music by Iconnic from the Noun Project
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    @dmurgaPeople by ProSymbolsfrom the Noun Project Music by Iconnic from the Noun Project
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    @dmurgaPeople by ProSymbolsfrom the Noun Project Music by Iconnic from the Noun Project
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    @dmurgaPeople by ProSymbolsfrom the Noun Project Music by Iconnic from the Noun Project
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    Challenges for MLPortfolios 1. Misplaced modelling. 2. Crude tools. 3. Under-supported people.
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    A Framework forthe ML Product Lifecycle
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    @dmurga Research Discovery Fundamental Delivery Applied Kindsof R&D Work Development Sure it’s possible? Sureit’svaluable?
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    @dmurga Research Discovery Fundamental Delivery Applied Kindsof R&D Work Development Unknown to World Known to World Sure it’s possible? Known to Our Organization Sureit’svaluable?
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    @dmurga Research Discovery Fundamental Delivery Applied Kindsof R&D Work Development Experimental Hypothesized Unknown Known Sureit’svaluable? Unknown to World Known to World Sure it’s possible? Known to Our Organization
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    @dmurga Research Discovery Fundamental Delivery Applied Kindsof R&D Work: Examples Development Experimental Hypothesized Unknown Known Sureit’svaluable? Unknown to World Known to World Sure it’s possible? Known to Our Organization
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    @dmurga Research Discovery Fundamental Delivery Applied Kindsof R&D Work: Examples Development Experimental Hypothesized Unknown Known Sureit’svaluable? Unknown to World Known to World Sure it’s possible? Known to Our Organization
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    @dmurga Research Discovery Fundamental Delivery Applied Kindsof R&D Work: Examples Development Experimental Hypothesized Unknown Known Sureit’svaluable? Unknown to World Known to World Sure it’s possible? Known to Our Organization
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    @dmurga Research Discovery Fundamental Delivery Applied Kindsof R&D Work: Examples Development Experimental Hypothesized Unknown Known Sureit’svaluable? Unknown to World Known to World Sure it’s possible? Known to Our Organization
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    @dmurga Research Discovery Fundamental Delivery Applied Kindsof R&D Work: Examples Development Experimental Hypothesized Unknown Known Sureit’svaluable? Unknown to World Known to World Sure it’s possible? Known to Our Organization
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    @dmurga Research Discovery Fundamental Delivery Applied Kindsof R&D Work: Examples Development Experimental Hypothesized Unknown Known Sureit’svaluable? Unknown to World Known to World Sure it’s possible? Known to Our Organization
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    @dmurga Research Discovery Fundamental Delivery Applied Kindsof R&D Work: Examples Development Experimental Hypothesized Unknown Known Sureit’svaluable? Unknown to World Known to World Sure it’s possible? Known to Our Organization
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    @dmurga Research Discovery Fundamental Delivery Applied MLProduct Lifecycle Development Experimental Hypothesized Unknown Known Sureit’svaluable? Unknown to World Known to World Sure it’s possible? Known to Our Organization
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    @dmurga Research Discovery Fundamental Delivery Applied MLProduct Lifecycle Development Experimental Hypothesized Unknown Known Sureit’svaluable? Unknown to World Known to World Sure it’s possible? Known to Our Organization No New ML
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    @dmurga Research Discovery Fundamental Delivery Applied MLProduct Lifecycle Development Experimental Hypothesized Unknown Known Sureit’svaluable? Unknown to World Known to World Sure it’s possible? Known to Our Organization No New ML Proto ML Product
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    @dmurga Research Discovery Fundamental Delivery Applied MLProduct Lifecycle Development Experimental Hypothesized Unknown Known Sureit’svaluable? Unknown to World Known to World Sure it’s possible? Known to Our Organization No New ML Proto ML Product M.V. ML Product
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    @dmurga Research Discovery Fundamental Delivery Applied MLProduct Lifecycle Development Experimental Hypothesized Unknown Known Sureit’svaluable? Unknown to World Known to World Sure it’s possible? Known to Our Organization Mature ML Product No New ML Proto ML Product M.V. ML Product
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    @dmurga Research Discovery Fundamental Delivery Applied MLProduct Lifecycle Development Experimental Hypothesized Unknown Known Sureit’svaluable? Unknown to World Known to World Sure it’s possible? Known to Our Organization Mature ML Product v2 and beyond No New ML Proto ML Product M.V. ML Product
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    @dmurga Research Delivery Applied Alternative MLProduct Lifecycle Development Experimental Hypothesized Unknown Known Sureit’svaluable? Unknown to World Known to World Sure it’s possible? Known to Our Organization Mature ML Product Proto ML Product Academic Results M.V. ML Product Industrial Lab Results Discovery Fundamental
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    @dmurga Research Discovery Fundamental Delivery Applied PreferredML Product Lifecycle Development Experimental Hypothesized Unknown Known Sureit’svaluable? Unknown to World Known to World Sure it’s possible? Known to Our Organization Mature ML Product v2 and beyond No New ML Proto ML Product M.V. ML Product
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    Challenges for MLPortfolios 1. Misplaced modelling.
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    @dmurgaPeople by ProSymbolsfrom the Noun Project Music by Iconnic from the Noun Project
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    @dmurgaPeople by ProSymbolsfrom the Noun Project Music by Iconnic from the Noun Project
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    @dmurgaPeople by ProSymbolsfrom the Noun Project Music by Iconnic from the Noun Project
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    @dmurgaPeople by ProSymbolsfrom the Noun Project Music by Iconnic from the Noun Project
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    @dmurgaPeople by ProSymbolsfrom the Noun Project Music by Iconnic from the Noun Project
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    @dmurgaPeople by ProSymbolsfrom the Noun Project Music by Iconnic from the Noun Project
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    @dmurgaPeople by ProSymbolsfrom the Noun Project World by Guilherme Furtado from the Noun Project
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    @dmurgaPeople by ProSymbolsfrom the Noun Project World by Guilherme Furtado from the Noun Project
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    @dmurgaPeople by ProSymbolsfrom the Noun Project World by Guilherme Furtado from the Noun Project
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    @dmurgaPeople by ProSymbolsfrom the Noun Project World by Guilherme Furtado from the Noun Project
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    @dmurgaPeople by ProSymbolsfrom the Noun Project World by Guilherme Furtado from the Noun Project Global: More data which changes relatively slowly. Local: Less data which changes relatively quickly.
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    @dmurgaPeople by ProSymbolsfrom the Noun Project World by Guilherme Furtado from the Noun Project Local Models Global Models
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    @dmurgaPeople by ProSymbolsfrom the Noun Project World by Guilherme Furtado from the Noun Project Global Models Local Models
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    @dmurgaPeople by ProSymbolsfrom the Noun Project World by Guilherme Furtado from the Noun Project M.V. ML Product No New ML Proto ML Product Mature ML Product v2 and beyond More Global More Local ML Product Lifecycle ModelCombination
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    @dmurgaPeople by ProSymbolsfrom the Noun Project World by Guilherme Furtado from the Noun Project M.V. ML Product No New ML Proto ML Product Mature ML Product v2 and beyond Progress from more global to more local models. ML Product Lifecycle More Global More Local ModelCombination
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    @dmurgaPeople by ProSymbolsfrom the Noun Project World by Guilherme Furtado from the Noun Project M.V. ML Product No New ML Proto ML Product Mature ML Product v2 and beyond Progress from more global to more local models. ML Product Lifecycle More Global More Local ModelCombination
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    @dmurgaPeople by ProSymbolsfrom the Noun Project World by Guilherme Furtado from the Noun Project M.V. ML Product No New ML Proto ML Product Mature ML Product v2 and beyond Progress from more global to more local models. ML Product Lifecycle More Global More Local ModelCombination
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    @dmurgaPeople by ProSymbolsfrom the Noun Project World by Guilherme Furtado from the Noun Project M.V. ML Product No New ML Proto ML Product Mature ML Product v2 and beyond Progress from more global to more local models. ML Product Lifecycle More Global More Local ModelCombination
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    @dmurgaPeople by ProSymbolsfrom the Noun Project World by Guilherme Furtado from the Noun Project M.V. ML Product No New ML Proto ML Product Mature ML Product v2 and beyond Progress from more global to more local models. ML Product Lifecycle More Global More Local ModelCombination
  • 56.
    Suggestions for MLPortfolios 1. Progress from global to local models.
  • 57.
    Challenges for MLPortfolios 1. Misplaced modelling. 2. Crude tools.
  • 58.
    @dmurgaPeople by ProSymbolsfrom the Noun Project Music by Iconnic from the Noun Project
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    @dmurgaPeople by ProSymbolsfrom the Noun Project Music by Iconnic from the Noun Project
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    @dmurgaPeople by ProSymbolsfrom the Noun Project Music by Iconnic from the Noun Project
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    Stages of MLWorkflow Offline Evaluation Feature Trans- formation Modeling Model Serving Online Evaluation Data Pre- processing Data set Validation Where to get your ML Tools?
  • 62.
    Stages of MLWorkflow Offline Evaluation Feature Trans- formation Modeling Model Serving Online Evaluation Data Pre- processing Data set Validation Where to get your ML Tools?
  • 63.
    Stages of MLWorkflow Offline Evaluation Feature Trans- formation Modeling Model Serving Online Evaluation Data Pre- processing Data set Validation Third Party Open Source or Vendor Your Team Your Organ- ization Where to get your ML Tools?
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    Stages of MLWorkflow Offline Evaluation Feature Trans- formation Modeling Model Serving Online Evaluation Data Pre- processing Data set Validation Third Party Open Source or Vendor Your Team Your Organ- ization Where to get your ML Tools?
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    Stages of MLWorkflow Offline Evaluation Feature Trans- formation Modeling Model Serving Online Evaluation Data Pre- processing Data set Validation Third Party Open Source or Vendor Your Team Your Organ- ization Where to get your ML Tools?
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    Stages of MLWorkflow Offline Evaluation Feature Trans- formation Modeling Model Serving Online Evaluation Data Pre- processing Data set Validation Third Party Open Source or Vendor Your Team Your Organ- ization Where to get your ML Tools?
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    Stages of MLWorkflow Offline Evaluation Feature Trans- formation Modeling Model Serving Online Evaluation Data Pre- processing Data set Validation Third Party Open Source or Vendor Your Team Your Organ- ization Share starting here Where to get your ML Tools?
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    Stages of MLWorkflow Offline Evaluation Feature Trans- formation Modeling Model Serving Online Evaluation Data Pre- processing Data set Validation Third Party Open Source or Vendor Your Team Your Organ- ization Share starting here Then here Where to get your ML Tools?
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    Stages of MLWorkflow Offline Evaluation Feature Trans- formation Modeling Model Serving Online Evaluation Data Pre- processing Data set Validation Third Party Open Source or Vendor Your Team Your Organ- ization Where to get your ML Tools? No New ML
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    Stages of MLWorkflow Offline Evaluation Feature Trans- formation Modeling Model Serving Online Evaluation Data Pre- processing Data set Validation Third Party Open Source or Vendor Your Team Your Organ- ization Where to get your ML Tools? No New ML Proto ML Product
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    Stages of MLWorkflow Offline Evaluation Feature Trans- formation Modeling Model Serving Online Evaluation Data Pre- processing Data set Validation Third Party Open Source or Vendor Your Team Your Organ- ization Where to get your ML Tools? M.V. ML Product No New ML Proto ML Product
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    Stages of MLWorkflow Offline Evaluation Feature Trans- formation Modeling Model Serving Online Evaluation Data Pre- processing Data set Validation Third Party Open Source or Vendor Your Team Your Organ- ization Where to get your ML Tools? M.V. ML Product No New ML Proto ML Product Mature ML Product
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    Stages of MLWorkflow Offline Evaluation Feature Trans- formation Modeling Model Serving Online Evaluation Data Pre- processing Data set Validation Third Party Open Source or Vendor Your Team Your Organ- ization Where to get your ML Tools? M.V. ML Product No New ML Proto ML Product Mature ML Product v2 and beyond
  • 74.
    Suggestions for MLPortfolios 1. Progress from global to local models. 2. Strategically invest in shared tooling.
  • 75.
    Challenges for MLPortfolios 1. Misplaced modelling. 2. Crude tools. 3. Under-supported people.
  • 76.
    @dmurgaPeople by ProSymbolsfrom the Noun Project Music by Iconnic from the Noun Project
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    @dmurgaPeople by ProSymbolsfrom the Noun Project Music by Iconnic from the Noun Project
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    @dmurgaPeople by ProSymbolsfrom the Noun Project Music by Iconnic from the Noun Project
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    @dmurgaPeople by ProSymbolsfrom the Noun Project Music by Iconnic from the Noun Project
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    @dmurgaPeople by ProSymbolsfrom the Noun Project Music by Iconnic from the Noun Project Two kinds of support: 1. Individual’s Skills 2. Team Structure
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    @dmurga M.V. ML Product No New ML ProtoML Product Mature ML Product v2 and beyond Drive ML (State-of-the-Art) Drive ML Inform ML Understand ML Skills Needed
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    @dmurga M.V. ML Product No New ML ProtoML Product Mature ML Product v2 and beyond Drive ML (State-of-the-Art) Drive ML Inform ML Understand ML Designer or User Researcher Other Engineers Data Scientist ML Engineer Product Manager Skills Needed
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    @dmurga M.V. ML Product No New ML ProtoML Product Mature ML Product v2 and beyond Drive ML (State-of-the-Art) Drive ML Inform ML Understand ML Designer or User Researcher Other Engineers Data Scientist ML Engineer Product Manager Skills Needed
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    @dmurga M.V. ML Product No New ML ProtoML Product Mature ML Product v2 and beyond Drive ML (State-of-the-Art) Drive ML Inform ML Understand ML Designer or User Researcher Other Engineers Data Scientist ML Engineer Product Manager Skills Needed
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    @dmurga M.V. ML Product No New ML ProtoML Product Mature ML Product v2 and beyond Drive ML (State-of-the-Art) Drive ML Inform ML Understand ML Designer or User Researcher Other Engineers Data Scientist ML Engineer Product Manager Skills Needed
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    @dmurga M.V. ML Product No New ML ProtoML Product Mature ML Product v2 and beyond Drive ML (State-of-the-Art) Drive ML Inform ML Understand ML Designer or User Researcher Other Engineers Data Scientist ML Engineer Product Manager Skills Needed
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    @dmurga M.V. ML Product No New ML ProtoML Product Mature ML Product v2 and beyond Drive ML (State-of-the-Art) Drive ML Inform ML Understand ML ML EngineerSkills Needed
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    @dmurga Roles ‣ Applied MLEng ‣ ML Tool Eng ‣ Core Researcher
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    @dmurga Roles ‣ Applied MLEng ‣ Product ‣ Domain (logs, text, recs,...) ‣ Experiments ‣ Systems (BE, DE) ‣ Algorithms ‣ ML Tool Eng ‣ Core Researcher
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    @dmurga Roles ‣ Applied MLEng ‣ Product ‣ Domain (logs, text, recs,...) ‣ Experiments ‣ Systems (BE, DE) ‣ Algorithms ‣ ML Tool Eng ‣ Infrastructure ‣ Algorithms ‣ Core Researcher
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    @dmurga Roles # Needed‣ AppliedML Eng ‣ Product ‣ Domain ‣ Experiments ‣ Systems ‣ Algorithms ‣ ML Tool Eng ‣ Infrastructure ‣ Algorithms ‣ Core Researcher
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    @dmurga M.V. ML Product No New ML ProtoML Product Mature ML Product v2 and beyond Drive ML (State-of-the-Art) Drive ML Inform ML Understand ML Applied ML Engineer ML Tools Engineer Skills Needed
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    @dmurga M.V. ML Product No New ML ProtoML Product Mature ML Product v2 and beyond Drive ML (State-of-the-Art) Drive ML Inform ML Understand ML Applied ML Engineer ML Tools Engineer Core ML Researcher Skills Needed
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    @dmurga M.V. ML Product No New ML ProtoML Product Mature ML Product v2 and beyond Integrated Isolated MLv.non-MLwork Team Structure
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    @dmurga M.V. ML Product No New ML ProtoML Product Mature ML Product v2 and beyond Integrated Isolated Central ML Squad ‣ More collaboration among MLers ‣ Harder to be product-aligned ‣ Possible deliverables: Models Systems Development effort MLv.non-MLwork Team Structure
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    @dmurga M.V. ML Product No New ML ProtoML Product Mature ML Product v2 and beyond Integrated Isolated Central ML Squad Cross-functional Squad ‣ Less collaboration among MLers, so need to be senior ‣ Easier to be product-aligned ‣ MLers likely to do non-ML They need to be flexible PM needs to be skilled to cross-prioritize MLv.non-MLwork
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    @dmurga M.V. ML Product No New ML ProtoML Product Mature ML Product v2 and beyond Integrated Isolated Central ML Squad Cross-functional Squad Separate ML Workstream ‣ Allows more focus when ML progress is more valuable ‣ Prioritization is higher-level: across streams, not tasks ‣ Lots of variety in structure and sharing MLv.non-MLwork
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    @dmurga M.V. ML Product No New ML ProtoML Product Mature ML Product v2 and beyond Integrated Isolated Central ML Squad Cross-functional Squad Separate ML Workstream Sibling Squad ‣ Even more focus for “step change” ‣ Need structure for alignment between siblings (eg., for online experimentation) ‣ Rare state since product discovery may be more valuable MLv.non-MLwork
  • 101.
    @dmurga M.V. ML Product No New ML ProtoML Product Mature ML Product v2 and beyond Integrated Isolated Central ML Squad Cross-functional Squad Separate ML Workstream Sibling Squad MLv.non-MLwork
  • 102.
    Challenges for MLPortfolios 1. Misplaced modelling. 2. Crude tools. 3. Under-supported people.
  • 103.
    Suggestions for MLPortfolios 1. Progress from global to local models. 2. Strategically invest in shared tooling. 3. Equip individuals and their teams.
  • 104.
    @dmurga Research Discovery Fundamental Delivery Applied PreferredML Product Lifecycle Development Experimental Hypothesized Unknown Known Sureit’svaluable? Unknown to World Known to World Sure it’s possible? Known to Our Organization Mature ML Product v2 and beyond No New ML Proto ML Product M.V. ML Product
  • 105.
    @dmurgaPeople by ProSymbolsfrom the Noun Project World by Guilherme Furtado from the Noun Project M.V. ML Product No New ML Proto ML Product Mature ML Product v2 and beyond Progress from more global to more local models. ML Product Lifecycle More Global More Local ModelCombination
  • 106.
    Stages of MLWorkflow Offline Evaluation Feature Trans- formation Modeling Model Serving Online Evaluation Data Pre- processing Data set Validation Third Party Open Source or Vendor Your Team Your Organ- ization Where to get your ML Tools?
  • 107.
    @dmurga M.V. ML Product No New ML ProtoML Product Mature ML Product v2 and beyond Drive ML (State-of-the-Art) Drive ML Inform ML Understand ML Designer or User Researcher Other Engineers Data Scientist ML Engineer Product Manager
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    @dmurga M.V. ML Product No New ML ProtoML Product Mature ML Product v2 and beyond Integrated Isolated Central ML Squad Cross-functional Squad Separate ML Workstream Sibling Squad MLv.non-MLwork
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  • 111.
    Thanks! Questions? David Murgatroyd(@dmurga) Suggestions: What kinds of ways can global and local models combine? What relation does org size have to tool source? How do you train Product Mgrs, Designers, etc., for ML product development? How does the ethics of ML Product Development fit? I hear you’re up for MassTLC’s ML in Action Award? What kind of ML roles are you hiring for in Boston? Hiring in Boston, NYC, London, and Stockholm!