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Shawn Scully - VP of Customer Success & Applicationsscully@dato.com @backwoodsbrains

Intelligent Applications with Machine Learning Toolkits

Within 5 years, every innovative application will be intelligent.

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Intelligent applications create tremendous value

…but take a lot of time & specialized skills to build.

RecommendersLead Scoring

Churn Prediction

Multi-channel TargetingAuto-Summarization

Fraud detectionIntrusion Detection

Demand Forecasting

Data MatchingFailure Prediction

Our mission is to

Accelerate innovators to create intelligent applications with agile machine learning.

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Needs of an Agile ML PlatformDato

Predictive Services

GraphLab Create

rapid development

deploy as microservice

live serving, monitoring, & model management

iterate w/feedback

A toolkit view of the world

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Algorithms vs. toolkitsSVD++ w/SGD

vs.SVD

Recommender• item similarity• SVD++• iALS• factorization machine• many more!• PhD students care a lot about these!

• many papers focused on “my curve is better than your curve”

• Not always the most practical…

• Grouped by a common task• Focused on meaningful differences in data &

problem• Practical implementations

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import graphlab as gl data = gl.SFrame.read_csv('my_data.csv')

model = gl.recommender.create(

data,

user_id='user',

item_id='movie’,

target='rating') recommendations = model.recommend(k=5)

cluster = gl.deploy.load(‘s3://path’)cluster.add(‘servicename’, model)

Easily create a live machine learning service

Create a Recommender

5 lines of code

Toolkit w/auto selection

Deploy in minutes

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Dato Machine Learning ToolkitsApplications• recommender• sentiment_analysis• similarity_search• churn_predictor• data_matching• lead_scoring• clickthrough_predictor

Fundamentals• regression• classifier• nearest_neighbors• clustering• deeplearning• anomaly_detection• pattern_mining• text_analytics• graph_analytics

Utilities• model_parameter_search• cross_validation• evaluation• comparison• feature_engineering

https://dato.com/products/create/docs/graphlab.toolkits.html

50+ models including factorization machines, convolutional neural nets, label propagation, & topic models all in one framework!

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Toolkit: Recommender

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Examples of Recommenders

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Recommend

Value: • Increase user engagement• Sell more/increase clickthrough• Create better user experiences

Goal: Find or recommend similar or related items.

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Recommend - Data + Toolkituser_id item_id item_name

103 1 ‘Empire Strikes Back’

102 2 ‘Wrath of Khan’

104 3 ‘Sleepless in Seattle’

102 4 ‘Rambo’

104 5 ‘Chocolate’

103 6 ‘The Avengers’

102 1 ‘Empire Strikes Back’

104 1 ‘Empire Strikes Back’

103 4 ‘Rambo’

104 7 ‘When Harry Met Sally’

102 2 ‘Wrath of Khan’

104 8 ‘Up’

recommendergraphlab.recommender.create

Toolkit: Sentiment Analysis & Product Sentiment

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Examples of sentiment scoring & summarization

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Sentiment Analysis & Product Sentiment

Value: • Quantitative measures from unstructured text• Eliminate the need to read everything• Summarize on aspects you care about

Goal: Score sentiment of a sentence, document, or aspect.

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Sentiment scoring- Data + Toolkit

sentiment_analysisgraphlab.sentiment_analysis.creategraphlab.product_sentiment.create

Toolkit: Similarity Search

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Examples of image search & tagging

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Image Search & Tagging

Value: • create more intuitive user experiences• learn interesting things like style• reduce manual processes (like tagging)

Goal: Find visually similar images.

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Image search - Data + Toolkit

similarity_searchgraphlab.data_matching.similarity_search.create

Toolkit: Churn Predictor

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Churn Prediction

Value: • Keep your customers• Optimize marketing/customer success spend• Identify issues with product or business

Goal: Identify users that are likely to stop doing something(e.g. paying for your service, using a product feature, etc.)

Confidential - GraphLab internal use only

Problem setup

Period 1

Period 2

Period 3

Features Target

Hold out set

Goal: model that predicts if a user does not appear in Period 2Evaluation: score for (app, user) pairs absent in Period 3 Machine

learningmodel

Evaluation

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Data Transformations

Time Uniquepairs

app user time etc app user feature1

feature2

Features:● time since last use● time since first use● # unique days user has used app● # times user used app in last delta days● Rolling aggregates● etc

Aggregate to generate predictive featuresopens

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Predict Churn - Data + Toolkituser_id event datetimestamp

103 play ‘01-01-15’

102 click ’02-05-15’

102 visit ‘03-06-15’

102 visit ’03-09-15’

103 purchase ’03-21-15’

103 click ’03-22-15’

102 click ’03-23-15’

103 click ’04-02-15’

103 play ‘04-01-15’

103 purchase ’05-02-15’

103 play ‘05-01-15’

103 play ’05-15-15’

churn_predictorgraphlab.churn_predictor.create

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Toolkit: Data Matching

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Examples of data matching

record= {‘SSN’:None, ‘Name’:’Smith, Will’ ‘DOB’:1973.01.02, ‘Sex’:’Male’, ‘ZIP;:94701}

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Data Matching

Value: • Deduplicate contacts/records• “360 view” of customer across multiple properties• Improve data quality

Goal: Identify entities & appropriately link records.

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Data matching – Data + Toolkit

data_matchinggraphlab.deduplication.creategraphlab.record_linker.create

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More than 50,000 developers are using Dato

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Dato Confidential - Do not Distribute

Tools built for innovators

The Agile Machine Learning Platform

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Agility to create machine learning services

GraphLab Create Application Toolkits:

• Auto-select the best algorithm• Auto-prepare the data for ML• Task-oriented methods

Data Layer for ML• Manipulate all-relevant data types• Out-of-core design eliminates scale

pains

Robust Enterprise-Grade Algorithms• 50+ of best-practice & novel

algorithms• Robust to real-world data

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Dato Predictive ServicesReal-time RecommendationsOnline Ad Scoring & ServingTransactional Fraud detection

Agility to deploy – Microservices on AWS, premises, Yarn

How will you make your enterprise intelligent?

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Thanks!

get the software!: https://www.dato.com/download/

platform overview: https://dato.com/products/

talk about ML at your company: scully@dato.com

Toolkits: overview:https://dato.com/products/create/docs/graphlab.toolkits.htmlrecommender: https://dato.com/products/create/docs/graphlab.toolkits.recommender.htmlchurn_predictor: https://dato.com/products/create/docs/graphlab.toolkits.churn_predictor.htmlsimilarity_search: https://dato.com/products/create/docs/graphlab.toolkits.data_matching.html#similarity-search-modelsentiment_analysis: https://dato.com/products/create/docs/graphlab.toolkits.sentiment_analysis.htmldata_matching: https://dato.com/products/create/docs/graphlab.toolkits.data_matching.html