Ciaburro / Joshi Python Machine Learning Cookbook,

Over 100 recipes to progress from smart data analytics to deep learning using real-world datasets
2. Auflage 2019
ISBN: 978-1-78980-075-3
Verlag: De Gruyter
Format: EPUB
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 642 Seiten

No detailed description available for "Python Machine Learning Cookbook,".

Autoren/Hrsg.

Ciaburro, Giuseppe

Joshi, Prateek

Fachgebiete

• Naturwissenschaften Biowissenschaften Angewandte Biologie Bioinformatik
• Mathematik | Informatik EDV | Informatik Angewandte Informatik Bioinformatik
• Mathematik | Informatik EDV | Informatik Technische Informatik Hardware: Grundlagen und Allgemeines

Inhaltsverzeichnis

Table of Contents - The Realm of Supervised Learning
- Constructing a Classifier
- Predictive Modeling
- Clustering with Unsupervised Learning
- Visualizing Data
- Building Recommendation Engines
- Analyzing Text Data
- Speech Recognition
- Dissecting Time Series and Sequential Data
- Image Content Analysis
- Biometric Face Recognition
- Reinforcement Learning Techniques
- Deep Neural Networks
- Unsupervised Representation Learning
- Automated machine learning and Transfer learning
- Unlocking Production issues

Über Autor(innen)

Ciaburro Giuseppe:

Giuseppe Ciaburro holds a PhD and two master's degrees. He works at the Built Environment Control Laboratory - Università degli Studi della Campania "Luigi Vanvitelli". He has over 25 years of work experience in programming, first in the field of combustion and then in acoustics and noise control. His core programming knowledge is in MATLAB, Python and R. As an expert in AI applications to acoustics and noise control problems, Giuseppe has wide experience in researching and teaching. He has several publications to his credit: monographs, scientific journals, and thematic conferences. He was recently included in the world's top 2% scientists list by Stanford University (2022).Joshi Prateek:

Prateek Joshi is the founder of Plutoshift and a published author of 9 books on Artificial Intelligence. He has been featured on Forbes 30 Under 30, NBC, Bloomberg, CNBC, TechCrunch, and The Business Journals. He has been an invited speaker at conferences such as TEDx, Global Big Data Conference, Machine Learning Developers Conference, and Silicon Valley Deep Learning. Apart from Artificial Intelligence, some of the topics that excite him are number theory, cryptography, and quantum computing. His greater goal is to make Artificial Intelligence accessible to everyone so that it can impact billions of people around the world.