Machine Learning-Guided Treatment Discovery

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Related lectures (31)

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World of Data: Machine Learning and Value Chain

Delves into machine learning, data insights, and commercial value in the digital world.

Data Mining: Introduction

Covers the challenges and opportunities of data mining, practical questions, algorithm components, and applications like shopping basket analysis.

Decision Trees and Random Forests: Concepts and Applications

Discusses decision trees and random forests, focusing on their structure, optimization, and application in regression and classification tasks.

Smart, Connected Products

Explores smart, connected products and their transformative impact on companies, covering artificial intelligence, machine learning, predictive models, forecasting methods, and more.

Introduction to Machine Learning

Covers the basics of machine learning, including supervised and unsupervised learning, linear regression, and classification.

Introduction to Data Science

Introduces the basics of data science, covering decision trees, machine learning advancements, and deep reinforcement learning.

Linear Regression: Foundations and Applications

Introduces linear regression, covering its fundamentals, applications, and evaluation metrics in machine learning.

Generative Models: Advancements in Molecular Design

Explores the use of generative models for discovering novel molecules in molecular design.

Machine Learning-Guided Treatment Discovery

Explores personalized medicine, machine learning for treatment prediction, and challenges in traditional algorithms.

Automated Chemical Synthesis: Catalyst Design & Optimization

Delves into the automation of chemical synthesis through catalyst discovery and optimization using machine learning and computational chemistry.