Knowledge is everything!
Sign up for our newsletter to receive:
- 10% off your ticket!
- insights, interviews, tips, news, and much more about Machine Learning Week Europe
- price break reminders
2020, year of the corona crisis, made it clear: data & analytics are key drivers for the future. Not only in healthcare, where deep learning helped to detect corona infections and machine learning predicted the spread of the infections, but also in industry and business: predictive analytics enabled companies to secure the supply chain of essential goods or to identify new buying behaviour quicker than ever before. And 2020 also changed the conference business itself, because virtual conferences demand completely new, interactive and holistic formats:
Welcome to Machine Learning Week Europe Virtual Livestream 2021!
The week of June 14th to 18th hundreds of data scientists, analytics managers and AI visionaries from pharma, manufacturing, marketing, insurance, and many more sectors will meet for keynotes and extensive expert exchanges at 6 conferences on 5 days discussing the 4 key topics with the 3 best topic experts. Each expert will present the 10 most important insights on 10 slides in 10 minutes followed by an intensive discussion panel and Q&A with the participants. In addition, each conference will be opened by a keynote. Join the expert rounds, apply for speaking or register for participating.
We provide a regional platform for the European data science community to share their success stories and insights with their industry peers. Five well established conferences, PAW Business, PAW Financial, PAW Healthcare, PAW Industry 4.0 and Deep Learning World, plus one new topic, PAW Climate, are running across the week. Don’t miss these five days, that will provide the perfect platform for in-depth knowledge-sharing, interactive, expert discussions and intensive industry networking.
Marketing & Sales
E-Commerce & Online-Marketing:
Data Engineering & Model Management
Data Management & Strategy
HR & E-Learning
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
There is a wealth of expertise, passion, and money pouring into climate tech as both startups and established industrial players seek to address one of the most important challenges facing humanity. Machine learning can be an important component in tech for addressing the climate crisis. Companies apply machine learning to problems such as:
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, the 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 all the verticals together for the first time in 2021.
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.
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.
Yes. Data mining is often used synonymously with predictive analytics, and, in any case, predictive analytics is a type of data mining.
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.
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.
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.
No. Machine Learning Week provides a balanced view of predictive analytics methods and tools across software vendors and solution providers.
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.
For speaker information and proposal submissions, click here.