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Learn JMP

The one place to access all JMP learning materials

Featured Items

Predictive Modeling and Machine Learning

  • Boosting Your Renewable System Performance

    Do you need to make sense of sensor or other sequential measurement data where the responses are not single points, but a range of points presented as curves? Do you need to use that data to predict the likelihood of a system failure or maintain consistent power quality for a renewable energy or other systems? Would you like examples of how to use software to analyze the impact of, and interaction...

    gail_massari gail_massari
    Learn JMP Events |
    Friday, August 1, 2025
    Aug 1

  • Advanced Analytics and Deep Learning in Chemistry

      With the JMP Student Edition, academic researchers get no-cost access to all JMP Pro capabilities, such as Python integration and more advanced tools for building machine learning models. This webinar will demonstrate advanced analytical applications for researchers in Chemistry, Chemical Engineering, Materials Science, and related fields by enhancing JMP Student Edition’s native features with...

    Ross_Metusalem Ross_Metusalem
    Learn JMP Events |
    Wednesday, June 11, 2025

  • Predictive Modeling in JMP

    (view in My Videos)

    DonMcCormack DonMcCormack
    Learning Center |
    Jun 3, 2025 5:34 PM
    166 views | 0 replies

  • JMP for Teaching Statistics in Semiconductor Engineering Education

        Get JMP software free for academic use at jmp.com/student   Semiconductor engineering is a data intensive process. Engineers need to visualize and analyze vast amounts of data to improve yield, identify and rectify drifts or failures, monitor process health, and more. JMP statistical software, used widely in the semiconductor industry, is a strong tool for teaching students in semiconductor ...

    Ross_Metusalem Ross_Metusalem
    Learn JMP Events |
    Thursday, April 17, 2025

  • Teaching Predictive Modeling

      Get JMP software free for academic use at jmp.com/student   Predictive modeling encompasses a range of techniques for using historical data to predict future outcomes, and it has applications in nearly all quantitative disciplines. The JMP Student Edition has robust predictive modeling capabilities, including a range of algorithms for classification and regression, automated model cross-valida...

    Ross_Metusalem Ross_Metusalem
    Learn JMP Events |
    Thursday, April 3, 2025

  • Removing the Guesswork for Handling Collinearity in Your Models - Mastering JMP

    Video was recorded in March 2025 using JMP 18 and JMP Pro 18.   Do you work with complicated processes where possible unaccounted-for variables might be impacting your predictions? Do you sometimes struggle to identify the validity of factors impacting the results of complicated interactions? Are collinear factors thwarting the efficiency of your process improvement projects?   In this Mastering J...

    gail_massari gail_massari
    Learn JMP Events |
    Friday, March 28, 2025

  • JMP for Teaching Data Analytics

      Get JMP software free for academic use at jmp.com/student   Data analytics courses are a core part of curricula in business, marketing, information systems, and related fields. These courses frequently cover a range of data analysis techniques, from basic data visualization and analysis through advanced methods that can include machine learning, time series forecasting, or text mining, to name...

    Ross_Metusalem Ross_Metusalem
    Learn JMP Events |
    Thursday, March 20, 2025

  • JMPをマスターしよう 「PLS回帰」編　オンデマンド版（日本語）

    2025/2/13に実施したWebセミナーのオンデマンド版です。 オンデマンド用に再録画し、編集をしております。すべての動画を50分程度で視聴できます。   目次 Chapter 1.PLS回帰の概要 Chatepr 2.PLS回帰の基本操作とレポート Chapter 3. PLS回帰を用いた分析事例 Chapter 4. PLS回帰での予測精度向上を目指して     Chapter 1. PLS回帰の概要（8分30秒） PLS回帰とはPLS回帰を用いると有効なケースPLS回帰における良いモデルの構築、因子数の設定 (view in My Videos)   Chapter 2. PLS回帰の基本操作とレポート Section 1.　基本操作とレポート　その1（12分25秒） 因子数の決定デフォルトで表示されるレポート（説明される変動、モデル係数など）負荷量プロット、スコアプロット、バイプ...

    Masukawa_Nao Masukawa_Nao
    Learn JMP Events |
    Thursday, February 13, 2025

  • JMPをマスターしよう　「モデルのあてはめ」活用編　オンデマンド（日本語）

    JMPの「モデルのあてはめ」プラットフォームは、データに統計モデル（回帰、分散分析など）をあてはめ、目的変数と説明変数との関係性やパターンを分析できます。本セミナーでは、この「モデルのあてはめ」でできることに焦点をあて、基本的な操作方法、レポートの解釈、多重共線性について説明します。   ※2024年12月5日に実施した同タイトルのセミナーのオンデマンドバージョンです。内容を基本操作と多重共線性に絞ってオンデマンド化しています。下記のチャプター番号と動画のチャプター番号が対応していない箇所がございます。あらかじめください。 ※セミナー実施時点での最新バージョン「JMP 18.1.1」を使用しています。 ※オンデマンド版の配布資料をダウンロードできます（jmp-fitmodel-ondemand.pdf）。   目次 イントロダクション（3分32秒） Chapter1. 基本的な操作の流れと...

    Masukawa_Nao Masukawa_Nao
    Learn JMP Events |
    Sunday, January 5, 2025

  • Oversampling in predictive modeling

    This video is a supplement to the Predictive Modeling using JMP Pro course. It shows an example of how oversampling for classification works, both undersampling from the majority target level and oversampling from the minority level. It also demonstrates how to adjust the predicted probabilities for the sampling.  You might also be interested in the Imbalanced Classification Add-In, which was disc...

    Di_Michelson Di_Michelson
    Learning Center |
    Nov 11, 2024 2:07 PM
    1643 views | 2 replies

  • Which Model When?

    The models you use depend on your data, the questions you are trying to answer and the problems you want to solve. See how to decide by working through case studies that illustrate how to identify, fit and evaluate models that might be most useful in achieving your analysis goal.     (view in My Videos) Questions answered by Olivia Lippincott @O_Lippincott and Andrea Coombs @andreacoombs1  at the ...

    andreacoombs andreacoombs
    Learn JMP Events |
    Tuesday, February 27, 2024

  • Funktionaler Datenexplorer für Spektraldaten (JMP Pro)

    Seit der Einführung des Funktionalen Datenexplorers (FDE) in JMP Pro 14 ist er zu einem unverzichtbaren Tool für die Zusammenfassung von Formmerkmalen und die Erkenntnisgewinnung geworden. Mit der Veröffentlichung von JMP Pro 17 haben wir zudem neue Werkzeuge hinzugefügt, die die Arbeit mit Spektraldaten erleichtern. Insbesondere das neue Wavelets-Modell bietet eine schnelle Alternative zu bestehe...

    Ryan_Gilmore Ryan_Gilmore
    Learn JMP Events |
    Friday, October 20, 2023

  • Modeling Mixed Effects for Binary and Count Response Data using Generalized Linear Mixed Models (GLMM)

    Generalized Linear Mixed Models were introduced in JMP Pro 17, where you  specify two distributions - Binomial and Poisson.    GLMM  combines two approaches: the linear mixed model and generalized linear model frameworks . GLMM is useful for three types of model structures: Randomized complete and incomplete block designsSplit-plot experimentsRandom coefficient models   See how to: Model mixed ef...

    jiancao jiancao
    Learn JMP Events |
    Friday, July 14, 2023

  • Using Prediction Profiling to Maximize Model Proficiency – Part 2

        See how to: ID new JMP 17 capabilites, including JMP extrapolation controlCustomize Profiler appearanceShare Profilers as HTMLUse the Interaction Profiler to show or hide interaction plots that update as you update the factor values in the Prediction ProfilerUse the Surface Profiler to produce a surface plot for the fitted modelUse the Simulator in the profilers to define random inputs, run s...

    gail_massari gail_massari
    Learn JMP Events |
    Monday, July 3, 2023

  • 関数データエクスプローラの概要　～関数主成分分析とさまざまな利用事例～　（日本語）

    関数データエクスプローラの概要と関数主成分分析（5分34秒）利用例１：関数データを用いたサンプルの分類 （16分52秒）利用例2：関数データを用いた特性値の予測（12分49秒）利用例3：関数応答実験計画（11分27秒）利用例4：スペクトルデータの分析（12分29秒） 「関数データエクスプローラ」（FDE; Functional Data Explorer）プラットフォームは、関数データ・シグナルデータ・時系列データを分析するためのプラットフォームです。関数データに対し、特徴を表す関数主成分を抽出して次元縮小をおこない、関数データの判別、予測モデルの作成などを行なえます。 本動画に関する資料（PDF)　をダウンロードできます。   関数データエクスプローラの概要と関数主成分分析（5分34秒） 関数データについて、関数データの特徴量として関数主成分を抽出すること。この後に説明する、利用例1～利...

    Ryan_Gilmore Ryan_Gilmore
    Learn JMP Events |
    Wednesday, December 21, 2022

  • Developer Tutorial: Modeling Spectral Data Using JMP Pro 17

    JMP Pro makes it easy to solve many kinds of problems involving data that is inherently functional in form, such as: Time series dataSensor streams from manufacturing processesMeasurements taken over a range of temperaturesSpectra: IR, Chromatography, Mass Spec, Nuclear Magnetic Resonance (view in My Videos)   See an overview of the basics of functional data analysis, with emphasis on  analyzing f...

    chris_gotwalt1 chris_gotwalt1
    Learn JMP Events |
    Friday, December 9, 2022

  • Identifying the Impact Curved Factor Shapes have on Responses

    This video was updated in August 2024.   Sampling points from curved data typically is not the most accurate way to create a predictive model. In many cases the sampled points miss variability that could impact outcome.  This demo uses a case study to show how to use JMP functional Data Explorer to address this challenge.   (view in My Videos) The Case Study: Use spectra to determine factors that...

    Peter_Hersh Peter_Hersh
    Learn JMP Events |
    Monday, May 23, 2022

  • Building Predictive Models for Spectral Data

    (view in My Videos)   Use JMP Pro to build a sustainable empirical model based on spectral data/wavelengths.   See how to: Examine data using Graph Builder to get idea of what different spectra look likeUse Multivariate Analysis to examine all wave lengths and resulting Correlation Coefficients to confirm multicolinearityUse Model-Driven Multivariate Control Charts to examine all wave lengths var...

    gail_massari gail_massari
    Learn JMP Events |
    Monday, May 9, 2022

  • Developer Tutorial: Using JMP Pro Generalized Regression to Better Understand Observational Data

    clay_barker clay_barker
    Learn JMP Events |
    Friday, November 12, 2021

  • Deriving Sentiments from Opinions or Product Choices

    (view in My Videos) See how to: Quantify positive or negative sentiment in unstructured text dataUnderstand basics of Lexical Sentiment Analysis Scores sentiment from individual words in each doc when no external measure of sentiment is availableUses a Sentiment dictionary (aka "lexicon") that specifies scores (e.g., wonderful = +90, disappointed = -30)Scores individual sentiment phrase to calcul...

    gail_massari gail_massari
    Learn JMP Events |
    Tuesday, October 6, 2020

  • Understanding and Applying Tree-based Methods for Predictor Screening and Modeling

      (view in My Videos) See how to: Model using Partition, Bootstrap Forests and Boosted TreeUnderstand pros and cons of decision trees Pros: Uncover non-linear relationships, get results that are easy to understand, screen large number of factors Cons: Handle one response at a time, forms if-then statement not mathematical formula, high variability can lead to major differences in a model for simi...

    gail_massari gail_massari
    Learn JMP Events |
    Tuesday, October 6, 2020

  • Discovering and Predicting Patterns Using Neural Network Models

      (view in My Videos) See how to: Understand a neural network as a function of a set of derived inputs, called hidden nodes, that are nonlinear functions of the original inputsInterpret Neural Network diagram inputs (factors) and outputs (responses) Understand terms and how they apply to building Neural Networks (nodes, activation type, activation functions)Understand types of activation function...

    gail_massari gail_massari
    Learn JMP Events |
    Thursday, September 24, 2020

  • Transforming Data to Make Better Predictions

      (view in My Videos)   See how to: Understand why transformations stabilize variance, make the error more uniform across the design region, remedy lack of fit and plot predictions in a way that does not violate physical limits, display negative counts or erroneously report yields as greater than 100%donnTransform data on the fly using Graph Builder and change scales to improve graph readability ...

    gail_massari gail_massari
    Learn JMP Events |
    Thursday, September 24, 2020

  • Using Generalized Regression in JMP® Pro to Create Robust Linear Models

    See how to: Understand the benefits of Generalized Regression (Penalized Regression) Use JMP Pro lasso and elastic net shrinkage techniques to reduce prediction variance, handle non-normal and zero-inflated responses, model mean responses and select the best model interactively. See how to: Use JMP Pro Quant...

    gail_massari gail_massari
    Learn JMP Events |
    Tuesday, September 22, 2020

  • Data Mining and Predictive Modeling

        (view in My Videos) See how to: Understand the manufacturing yield example used in the demoFind patterns Use Distribution to examine the relationship between variables and between variables and responseUse Graph Builder to examine all variables, use icon drag-and-drop to fit lines to data, turn on statistics like R square, change fit type interactively and add color to highlight key findings ...

    gail_massari gail_massari
    Learn JMP Events |
    Monday, September 21, 2020
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