Unser Katalog

Machine Learning Evaluation: Towards Reliable and Responsible AI

Partially Observed Markov Decision Processes : Filtering, Learning and Controlled Sensing

Machine and Deep Learning Using MATLAB : Algorithms and Tools for Scientists and Engineers

Machine Learning with PyTorch and Scikit-Learn : Develop machine learning and deep learning models with Python

Maschinelles Lernen für Dummies

Hands-On Machine Learning with Scikit-Learn, Keras , and TensorFlow

Machine Learning with R : Learn techniques for building and improving machine learning models, from data preparation to model tuning, evaluation, and working with big data

Probabilistic machine learning : advanced topics

The Handbook of Data Science and AI : Generate Value from Data with Machine Learning and Data Analytics

Data-Driven Science and Engineering : Machine Learning, Dynamical Systems, and Control

Deep Learning for Physical Scientists : Accelerating Research with Machine Learning

Deep Learning with Python

Machine Learning : A First Course for Engineers and Scientists

Machine Learning with PyTorch and Scikit-Learn : Develop machine learning and deep learning models with Python

Tidy Modeling with R

Codeless Deep Learning with KNIME : Build, train, and deploy various deep neural network architectures using KNIME Analytics Platform

Machine Learning for Engineers : Using Data to Solve Problems for Physical Systems

Quantum Science and Technology
Machine Learning with Quantum Computers

Reinforcement Learning : An Introduction

Maschinelles Lernen : Grundlagen und Algorithmen in Python