Machine Learning Week Europe
Join us to learn more about the latest developments in Predictive Analytics and Deep Learning

Machine Learning Week Europe 2023 will take place in November in Berlin. The exact date and venue will be announced soon.

Welcome to Machine Learning Week Europe 2023!

In 2023, Machine Learning Week is live in Berlin, packed with two days about the newest insights in Predictive Analytics for Business, Industry 4.0 and Deep Learning. In addition, we offer a series of deep dive workshops on the day after the conference.




Hundreds of data scientists, analytics managers and AI visionaries from pharma, manufacturing, marketing, insurance, and many more sectors will meet for keynotes, case studies, deep dives and table discussions on 2 days. Join the conference or apply for speaking.


We provide a regional platform for the European data science community to share their success stories and insights with their industry peers. At Machine Learning Week Europe, we cover topics of Predictive Analytics for Business, Predictive Analytics for Industry 4.0, and Deep Learning World. Don’t miss these two days, that provide the perfect opportunity for in-depth knowledge-sharing, interactive, expert discussions and intensive industry networking.

  • Technologies
    • Machine ~, Ensemble ~ & Deep Learning
    • Transfer ~, Reinforcement ~ & One-Shot-Learning
    • Internet of Things & Smart Devices
    • Data, Stream, Text, Process & Network Mining
    • Times Series Models
    • Bayesian Learning
    • Ensemble Learning
    • Transfer Learning
    • Reinforcement Learning
    • RNN, CNN & GAN
    • Markov Chain Monte Carlo simulations
    • … and more!
  • Business Applications

    Marketing & Sales

    • Marketing Mix Modelling
    • Predictive Lead Scoring
    • Customer Lifetime Value
    • Affinity Scoring
    • Churn Prevention
    • Chat Bots
    • Dynamic & Multitouch Attribution
    • Marketing Mix Modelling
    • Churn Prediction & Prevention
    • Customer Lifetime Value
    • Lead & Affinity Scoring
    • Customer Segmentation vs. Persona
    • Demand & Revenue Forecast
    • Response & Uplift Modelling
    • Recommender Systems

    E-Commerce & Online-Marketing:

    • Dynamic Attribution
    • Dynamic Pricing
    • Dynamic Couponing
    • Bid Optimization
    • Website Personalization

    Data Engineering & Model Management

    • Data Lakes & Pipelines
    • Data & Software Architecture
    • Model Automation & Evaluation
    • Feature Engineering & Management
    • Microservices & Data/Model-as-a-Service

    Data Management & Strategy

    • Data & Design Thinking
    • Customer Data Platforms & Data Management Platforms
    • Data Labs vs. Data Ops
    • Data Culture & Literacy
    • Meta Data & Data Quality Management
    • Data Sourcing & Governance

    HR & E-Learning

    • Risk Scoring
    • Fraud Detection
    • Anomaly Detection
    • Visual Inspection
    • Robo Advisory
  • Industrial Applications
    • Predictive & Prescriptive Maintenance
    • Object & Action Recognition
    • Visual Inspection & Damage Detection
    • Capacity Prediction & Optimization
    • Demand Forecasting & Predictive Inventory
    • Route & Stock Optimization
    • Autonomous Driving & Flying
    • Anomaly Detection & Root Cause Analysis
    • Fault Prediction & Failure Detection
    • Risk Prediction & Prevention
    • Energy Consumption & Generation Prediction
    • … and many more!
  • Financial, Banking, Insurance Applications
    • Risk Scoring
    • Fraud Detection
    • Anomaly Detection
    • Visual Inspection
    • Robo Advisory
  • Healthcare Applications

    Machine Learning:

    • Improves patient care
    • Reduces costs
    • Brings greater efficiencies to the healthcare industry


    • Clinical Decision & Diagnosis Support (CDS)
    • Disease & Cancer Detection
    • Rare Diseases Identification
    • Risk Prediction & Scoring
    • Customer / Patient Segmentation
    • Survival / Mortality Prediction
    • Fraud Detection
    • Readmission Reduction
    • Demand Forecast
    • Capacity & Staff Planning
    • Robotic Process Automation
    • Drug Discovery
    • Robotic Surgery
    • Personalized / Precision Medicine
    • Industry & Healthcare 4.0
    • … and many more!


    Predictive analytics addresses today’s pressing challenges in healthcare effectiveness and economics by improving operations across the spectrum of healthcare functions:

    Personalized medicine. Per-patient prediction and analytically enhanced diagnosis drives individual clinical treatment decisions

    Insurance. Predictively guided decisioning combats risk and renders insurance more equitable and profitable

    Hospital administration. Analytics detects and recoups loss due to fraud and waste

    Healthcare marketing. From medical suppliers to healthcare screening service providers, the performance of industry enterprises hinges on analytically targeted marketing

    Drug development. Analytics advances pharmaceutical engineering, testing, and other processes

    Much more. Other applications include predicting per-patient disease progression, mortality risk, availability of clinical trial participants, consumer prescription adherence, and more

  • Deep Learning Methods & Applications
    • Image & Object Recognition
    • Speech, Gesture & Character Recognition
    • Natural Language Processing & Generation
    • Entity Recognition & Text Extraction
    • Automatic Translation & Caption Generation
    • Forecasting & Event Detection
    • Visual Inspection & Action Recognition
    • Autonomous Driving & Flying
    • Recommender Systems
    • Chat Bots & Virtual Agents
    • Long Short-Term Memory (LSTM) Neural Networks
    • Recurrent Neural Networks (RNN)
    • Convolutional Neural Networks (CNN)
    • Generative Adversarial Networks (GAN)
    • Deep Reinforcement Learning (DRL)
    • Capsule Networks (CapsNet)
    • … and more.

Machine Learning Week — the facts:






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What our attendees think!

The Venue


The 2023 venue will be announced shortly

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  • What's the relationship between Machine Learning Week, Predictive Analytics World and Deep Learning World?

    Machine Learning Week evolved from the Predictive Analytics World (PAW) conferences, which began in 2009, running in multiple cities in Europe and the US each year. From 2018, in response to vendor and attendee requests to have one place they could meet everybody, various vertical conferences (PAW Business, PAW Industry 4.0, PAW Financial, PAW Healthcare), were brought together in one mega-event in Las Vegas. This was met with an overwhelmingly positive reception from all participants. Deep Learning World was also launched as part of the family in 2018 and PAW Climate in 2021.

    Machine Learning Week Europe is following the same path, bringing some verticals together.


  • What is predictive analytics?

    Predictive analytics optimizes marketing campaigns and website behavior to increase customer responses, conversions and clicks, and to decrease churn. Each customer’s predictive score informs actions to be taken with that customer — business intelligence just doesn’t get more actionable than that.

    Predictive analytics is business intelligence technology that produces a predictive score for each customer or other organizational element. Assigning these predictive scores is the job of a predictive model which has, in turn, been trained over your data, learning from the experience of your organization.

  • Is predictive analytics different from forecasting?

    Machine Learning Week often include select sessions on forecasting since it is a closely related area, and, in some cases, predictive analytics is used as a component to build a forecast model.
    However, predictive analytics is something else entirely, going beyond standard forecasting by producing a predictive score for each customer or other organizational element. In contrast, forecasting provides overall aggregate estimates, such as the total number of purchases next quarter. For example, forecasting might estimate the total number of ice cream cones to be purchased in a certain region, while predictive analytics tells you which individual customers are likely to buy an ice cream cone.

  • Is this a “data mining” conference?

    Yes. Data mining is often used synonymously with predictive analytics, and, in any case, predictive analytics is a type of data mining.

  • Is this a “data science” conference?

    Yes. Predictive analytics is a form of data science. Moreover, it is the most actionable form. A predictive model generates a predictive score for each individual, which in turn directly informs decisions for that individual, e.g., whether to contact, extend a retention offer, approve for credit, investigate for fraud, or apply a certain medical treatment. Rather than solely providing insights, predictive analytics directly drives or informs millions of operational decisions.

  • Is this a “big data” conference?

    Yes. Predictive analytics is a key method to truly leverage big data. At the center of the big data revolution is prediction. The whole point of data is to learn from it to predict. What is the value, the function, the purpose? Predictions drive and render more effective the millions of organizational operational decisions taken every day.

  • Is this an AI conference?

    Yes. Artificial intelligence (AI) is a broad, subjective term with many possible definitions—but by any definition, it always includes machine learning (predictive modeling) as an example of AI technology/capabilities.

  • Is Machine Learning Week run by a software vendor?

    No. Machine Learning Week provides a balanced view of predictive analytics methods and tools across software vendors and solution providers.

  • Is Machine Learning Week a research conference?

    No. Machine Learning Week is focused on today’s commercial deployment of predictive analytics, rather than academic or R&D activities. Separately, there are a number of research-oriented conferences; in predictive analytics’ commercial application, we are essentially standing on the shoulders of those giants known as researchers.

  • Are you considering new speakers for Machine Learning Week?

    For speaker information and proposal submissions, click here.

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