Unser Katalog

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

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

Maschinelles Lernen : Grundlagen und Algorithmen in Python

Data Science - was ist das eigentlich?! : Algorithmen des maschinellen Lernens verständlich erklärt

Studies in Big Data
Granular Computing Based Machine Learning : A Big Data Processing Approach

Machine Learning : A Constraint-Based Approach

Lecture Notes in Computer Science : Information Systems and Applications, incl. Internet/Web, and HCI
Machine Learning, Optimization, and Big Data : Third International Conference, MOD 2017, Volterra, Italy, September 14-17, 2017, Revised Selected Papers