Machine Learning with Mathematica

This course provides the foundational concepts in Machine Learning and Artificial Intelligence.It teaches about rapid prototyping of AI/ML models for solving tasks of various complexities with Mathematica.An 8 stage workflow for continuous development and deployment of AI/ML models is covered in detail.

Course ContentPart 1Machine Learning Overview

• Introduction to general concepts in Machine Learning

• Demonstrations of ML/AI functions in Mathematica

Machine Learning Pipeline

• 8 stage workflow for ML (Data Acquisition, Cleaning, Visualization, Transformation, Training, Cross-validation, Testing, Deployment)

• Developing an end-to-end ML model

Machine Learning Models

• Explanation of working of different models like linear regression, logistic regression, decision trees, random forests, etc.

• Deep dive into optimal training strategies (SGD, ADAM, etc.)

• Model parameters fine tuning methods (Grid search v/s Stochastic search)

Part 2Neural Networks

• Introduction to neural networks

• Demonstration of simple neural networks

Predictive Neural Networks

• Training neural networks for prediction tasks in various domains:

  • Image classification (Fixed dimension data)

  • Text Sentiment analysis (Variable dimension sequence data)

Generative Neural Networks

• Introduction to Autoencoders as the basis for generative models

• Overview of generative models in various domains:

  • Stable diffusion (Image generation)

  • Transformers (Text generation)

Dauer: 7 StundenSprache: englischMaterial: englischVoraussetzungen: Grundlegende Statistikkenntnisse, Grundkenntnisse in Mathematica, wie sie im Kurs "Mathematica Gurndlagen und Programmiertechniken" vermittelt werden

Rahmenbedingungen

• Geschult wird mit der aktuellen Software-Version.

• Bitte beachten Sie, dass Sie uns sowohl die Postanschrift als auch die E-Mail-Adresse der Teilnehmer mit der Beauftragung mitteilen.