Raschka / Mirjalili Python Machine Learning, Second Edition

Machine Learning and Deep Learning with Python, scikit-learn, and TensorFlow
2. Auflage 2017
ISBN: 978-1-78712-602-2
Verlag: De Gruyter
Format: PDF
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 622 Seiten

No detailed description available for "Python Machine Learning, Second Edition".

Autoren/Hrsg.

Raschka, Sebastian

Mirjalili, Vahid

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Neuronale Netzwerke
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Spracherkennung, Sprachverarbeitung

Inhaltsverzeichnis

Table of Contents - Giving Computers the Ability to Learn from Data
- Training Machine Learning Algorithms the Ability to Learn from Data
- A Tour of Machine Learning Classifiers Using Scikit-Learn
- Building Good Training Sets – Data Preprocessing
- Compressing Data via Dimensionality Reduction
- Learning Best Practices for Model Evaluation and Hyperparameter Tuning
- Combining Different Models for Ensemble Learning
- Applying Machine Learning to Sentiment Analysis
- Embedding a Machine Learning Model into a Web Application
- Predicting Continuous Target Variables

- Working with Unlabeled Data – Clustering Analysis
- Implementing a Multilayer Artificial Neural Network from Scratch
- Parallelizing Neural Network Training with TensorFlow
- Going Deeper: The Mechanics of TensorFlow
- Classifying Images with Deep Convolutional Neural Networks

- Modeling Sequential Data using Recurrent Neural Networks

Über Autor(innen)

Raschka Sebastian:

Sebastian Raschka is an Assistant Professor of Statistics at the University of Wisconsin-Madison focusing on machine learning and deep learning research. As Lead AI Educator at Grid AI, Sebastian plans to continue following his passion for helping people get into machine learning and artificial intelligence.Mirjalili Vahid:

Vahid Mirjalili is a deep learning researcher focusing on CV applications. Vahid received a Ph.D. degree in both Mechanical Engineering and Computer Science from Michigan State University.