Overview
Mathematica is a modern computing system for data analytics. Mathematica offers built in machine learning capabilities for data analysis.
This instructor-led, live training (online or onsite) is aimed at data scientists who wish to use machine learning in Mathematica for data analysis.
By the end of this training, participants will be able to:
- Build and train machine learning models.
- Import and prepare data for machine learning.
- Separate training data from test data.
- Explore deep learning and neural network applications in data analysis.
Format of the Course
- Interactive lecture and discussion.
- Lots of exercises and practice.
- Hands-on implementation in a live-lab environment.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
Requirements
- An understanding of Mathematica
Audience
- Data Scientists
Course Outline
Introduction
What is AI?
- Computational Psychology
- Computational Philosophy
Machine Learning
- Computational learning theory
- Computer algorithms for computational experience
Deep Learning
- Artificial neural networks
- Deep learning vs. machine learning
Preparing the Development Environment
- Installing and configuring Mathematica
Machine Learning
- Importing and separating data
- Normalizing and interpolating data
- Grouping and sorting elements
Predictors and Classifiers
- Working with a linear model
- Representing a data set
- Generating a sequence of values
Supervised Machine Learning
- Implementing supervised tasks
- Using the training data
- Measuring performance
- Identifying clusters
Summary and Conclusion