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Cyclo-E5-bridged trinuclear triple-decker complexes (E = P, As) containing a triply-bonded Mo2 unit and their isomerisation

Chemical communications (Cambridge, England), 2023-09, Vol.59 (75), p.11192-11195

2023

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Python Machine Learning

Lee, Wei-Meng

1, 2019

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Beginning Ethereum Smart Contracts Programming: With Examples in Python, Solidity, and JavaScript

Lee, Wei-Meng

1, 2019

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Beginning Ethereum Smart Contracts Programming: With Examples in Python, Solidity, and JavaScript

Lee, Wei-Meng

Second edition, 2023

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Robust multipath multicast routing algorithms for videos in Software-Defined Networks

2014 IEEE 22nd International Symposium of Quality of Service (IWQoS), 2014, p.218-227

2014

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Comparison of infliximab drug measurement across three commercially available ELISA kits

Pathology, 2016-10, Vol.48 (6), p.608-612

2016

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Vb.net Developer's Guide

1st ed., 2001

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Beginning Ethereum Smart Contracts Programming: With Examples in Python, Solidity, and JavaScript, Second Edition

Lee, Wei-Meng

Second Edition, 2023

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NET Mobile Web Developers Guide

Milroy, Steve

1, 2002

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C# .Net: Web developer's guide

2002

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Webmasters Guide to the Wireless Internet

Syngress

1, 2001

Volltextzugriff (PDF)

C#.Net Developer's Guide

Adrian Turtschi, Jason Werry, Greg Hack, Joseph Albahari

1, 2002

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Beginning Android programming

DiMarzio, Jerome

Fourth edition., 2016

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E-bridged trinuclear triple-decker complexes (E = P, As) containing a triply-bonded Mo unit and their isomerisation

Chemical communications (Cambridge, England), 2023-09, Vol.59 (75), p.11192-11195

2023

Volltextzugriff (PDF)

Cyclo -E 5 -bridged trinuclear triple-decker complexes (E = P, As) containing a triply-bonded Mo 2 unit and their isomerisation

Chemical communications (Cambridge, England), 2023-09, Vol.59 (75), p.11192-11195

2023

Volltextzugriff (PDF)

Using Azure Machine Learning Studio

Python Machine Learning, 2019

Lee, Wei-Meng

2019

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Manipulating Tabular Data Using Pandas

Python Machine Learning, 2019

Lee, Wei-Meng

2019

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Getting Started with Scikit-learn for Machine Learning

Python Machine Learning, 2019

Lee, Wei-Meng

2019

Volltextzugriff (PDF)

Unsupervised Learning—Clustering Using K-Means

Python Machine Learning, 2019

Lee, Wei-Meng

2019

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Supervised Learning—Classification Using Support Vector Machines

Python Machine Learning, 2019

Lee, Wei-Meng

2019

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Deploying Machine Learning Models

Python Machine Learning, 2019

Lee, Wei-Meng

2019

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Extending Python Using NumPy

Python Machine Learning, 2019

Lee, Wei-Meng

2019

Volltextzugriff (PDF)

Supervised Learning—Classification Using Logistic Regression

Python Machine Learning, 2019

Lee, Wei-Meng

2019

Volltextzugriff (PDF)

Introduction to Machine Learning

Python Machine Learning, 2019

Lee, Wei-Meng

2019

Volltextzugriff (PDF)

Supervised Learning—Linear Regression

Python Machine Learning, 2019

Lee, Wei-Meng

2019

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Cyclo-E5-bridged trinuclear triple-decker complexes (E = P, As) containing a triply-bonded Mo2 unit and their isomerisation

Python Machine Learning

Beginning Ethereum Smart Contracts Programming: With Examples in Python, Solidity, and JavaScript

Beginning Ethereum Smart Contracts Programming: With Examples in Python, Solidity, and JavaScript

Robust multipath multicast routing algorithms for videos in Software-Defined Networks

Comparison of infliximab drug measurement across three commercially available ELISA kits

Vb.net Developer's Guide

Beginning Ethereum Smart Contracts Programming: With Examples in Python, Solidity, and JavaScript, Second Edition

NET Mobile Web Developers Guide

C# .Net: Web developer's guide

Webmasters Guide to the Wireless Internet

C#.Net Developer's Guide

Beginning Android programming

E-bridged trinuclear triple-decker complexes (E = P, As) containing a triply-bonded Mo unit and their isomerisation

Cyclo -E 5 -bridged trinuclear triple-decker complexes (E = P, As) containing a triply-bonded Mo 2 unit and their isomerisation

Using Azure Machine Learning Studio

Manipulating Tabular Data Using Pandas

Getting Started with Scikit-learn for Machine Learning

Unsupervised Learning—Clustering Using K-Means

Supervised Learning—Classification Using Support Vector Machines

Deploying Machine Learning Models

Extending Python Using NumPy

Supervised Learning—Classification Using Logistic Regression

Introduction to Machine Learning

Supervised Learning—Linear Regression

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