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Predictive Analytics World is the leading vendor independent conference for applied machine learning for industry 4.0.
Business users, decision makers and experts in predictive analytics will meet on 11-12 May, 2020 in Munich to discover and discuss the latest trends and technologies in machine & deep learning for the era of Internet of Things and artificial intelligence.
Industry 4.0 has evolved from buzzword to reality. Previous years’ PAW conferences showed that major enterprises such as Roche or HP, mid-sized companies as Schaeffler or Bossard and also Start-Ups such as Konux or Bowery implemented Machine & Deep Learning solutions successfully. They also mastered a variety of challenges in order to put predictive models into production. Some even turned them into new products. The next phase of the Industry 4.0 analytics journey is about scaling development and operations of data products and about broadening the application of predictive & prescriptive analytics across all company departments and industries. In two parallel tracks, one featuring case studies and another one for deep dives, you will learn from successful data science projects and well-known experts how to master these challenges. Use this opportunity to discuss your questions with the speakers in extensive Q&A and exchange your professional experiences with your industry peers during multiple networking event formats. See you in May 2020 in Munich!
Attend Predictive Analytics World for Industry 4.0 and witness today’s rapidly emerging movement to fortify Industry 4.0 with big data’s biggest win: the power to predict (e.g. failures, load, demand & more). The premier cross-vendor networking event, this conference assembles the industry’s leaders to deliver case studies and expertise, revealing how predictive analytics:
Predictive Analytics World for Industry 4.0. provides unique learning and networking opportunities. Attendees come from industries such as:
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.
Predictive Analytics World 4.0 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. Predictive analytics means the commercial deployment of machine learning (the two terms are often used synonymously). Although the term “machine learning” used to be common only within the walls of research labs, it’s now also used more and more in the context of commercial deployment. Whichever term you prefer, we are discussing technology that learns from data to predict or infer an unknown, including decision trees, logistic regression, neural networks, and many other methods.
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. Predictive Analytics World provides a balanced view of predictive analytics methods and tools across software vendors and solution providers.
No. Predictive Analytics World 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.
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