Statistics, Predictive Modeling and Data Mining
- From Modelling to Deep LearningIn this webinar, we introduce novel ways to analyze image and text data to aid in classifying, predicting, and improving performance using deep learning methods that are simple to apply and master.
- Enhancing Insights: Image Analysis and Comprehensive Data Exploration in JMP® ProThis webinar demonstrates how to harness the power of data to predict trends, identify opportunities, and make informed decisions. Specifically, with JMP's predictive analytics software, JMP Pro.
- Workshop: Making better data-based decisions with statistical modelling techniquesThis two-part workshop has been designed for scientists and engineers who want to make the most of the data they have available. The workshop will guide you through the basics of predictive modelling, helping to drive innovation and process improvement.
- Lohmann: Elevate Science and Engineering with Predictive ModelingWatch this video and get the knowledge and tools you need to make data-driven decisions using Predictive Modeling.
- Make better data based decisions with Statistical Modelling TechniquesIn this fun, engaging and free three-part online training program on DoE, delivered by JMP, you will be introduced to DoE and discover how it enables scientists and engineers to develop better solutions faster.
- How to ensure your investment in Machine Learning yields beneficial outcomesHear Jonathan Williams, PhD, is the Data Analysis Manager at IQE. You will find guidance and stories about how to get started with machine learning techniques or effectively integrate them within existing programs that seek to make the most of your data and drive more value for your organization.
- The Art of Effective Statistical CollaborationDr. Julia Sharp and Dr. Emily Griffith discuss the art of effective statistical collaboration.
- Revolutionizing Sustainability Through Green ChemistryJoin us for a virtual discussion with Grace Lasker and Rick Morgan on sustainability through green chemistry.
- Glean and Visualize Deeper Insight from Your DataHear best practices from Procter & Gamble and Michelin! Gaining skills around a multistage process of turning data into useful insights is key. You will see how interactive, no-code analytics enable any scientist or engineer to turn data into actionable insights with a combination of data preparation.
- The Significance of Data Science EthicsHear from top researchers in the world of Astrophysics.
- Producers, Consumers, and Servicers: Three Perspectives on ReliabilityJerry Fish shares core reliability analysis techniques and best practices by walking through a hypothetical case study based on HVAC reliability.
- How to Model Complex, High-Dimensional Chemical SpectraBill Worley and Jeremy Ash demonstrate spectral analysis in JMP. Understanding and acting on factors influencing quality can result in reduced cost, faster time to market, better quality, and other benefits to your organization.
- How to Get the Most Out of Machine LearningHear from leaders in the machine learning realm from Brewer Science, Abt Associates and SAS
- Build - and Choose - Better Models Faster: Data Scientists in a BoxKemal Oflus demonstrates how to utilize machine learning methods without having to write and tune algorithms by leveraging your subject matter expertise.
- Predicting Product Reliability: A Case StudyExplore core reliability analysis techniques and best practices by walking through a case study based on hard drive reliability.
- Leveraging Free Text Data to Build Better ModelsLearn how text data can be combined with non-text data to build better models and make better decisions.
- Predictive Modeling for Risk of DiseaseWalk through an example based on building predictive models for peripheral arterial disease risk using data from the National Health and Nutrition Examination Surveys.
- Gaining Innovation Momentum Through Data AnalyticsIndustry 4.0, big data, data mining and IoT. As the digitization of the manufacturing sector gains momentum, what key things do you need to know about analyzing your manufacturing data?
- Interactive and Semi-Automated Reporting on the Safety and Efficacy of Clinical Studies - DIAIndustry 4.0, big data, data mining and IoT. As the digitization of the manufacturing sector gains momentum, what key things do you need to know about analyzing your manufacturing data?
- Worst Practices in Data MiningData mining expert Dick De Veaux discusses case studies from a range of industries to illustrate pitfalls that can frustrate problem-solving and discovery.
- Moving from SPSS to JMPTransitioning from SPSS to JMP? See how each software handles descriptive statistics, visualizations, bivariate tests, contingency tables and model building.