Building Machine Learning Systems with Python

This book provides you with an accessible route into Python machine learning, featuring a wealth of real-world examples.

**Tag(s):**
Machine Learning
Python

**Publication date**: 26 Jul 2013

**ISBN-10**:
1782161406

**ISBN-13**:
9781782161400

**Paperback**:
290 pages

**Views**: 3,010

Building Machine Learning Systems with Python

This book provides you with an accessible route into Python machine learning, featuring a wealth of real-world examples.

Note:

- Packt Publishing provides this book for free.

- You can download this book in ePub/Mobi/PDF formats or read it online.

- You're required to signup first.

From the Book Description:

- Packt Publishing provides this book for free.

- You can download this book in ePub/Mobi/PDF formats or read it online.

- You're required to signup first.

From the Book Description:

Coelho and Richert wrote:Machine learning, the field of building systems that learn from data, is exploding on the Web and elsewhere. Python is a wonderful language in which to develop machine learning applications. As a dynamic language, it allows for fast exploration and experimentation and an increasing number of machine learning libraries are developed for Python.

Building Machine Learning system with Python shows you exactly how to find patterns through raw data. The book starts by brushing up on your Python ML knowledge and introducing libraries, and then moves on to more serious projects on datasets, Modelling, Recommendations, improving recommendations through examples and sailing through sound and image processing in detail.

Using open-source tools and libraries, readers will learn how to apply methods to text, images, and sounds. You will also learn how to evaluate, compare, and choose machine learning techniques.

Written for Python programmers, Building Machine Learning Systems with Python teaches you how to use open-source libraries to solve real problems with machine learning. The book is based on real-world examples that the user can build on.

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About The Author(s)

Luis Pedro Coelho is a computational biologist. He works at the European Molecular Biology Laboratory (EMBL) in Peer Bork's group in microbial community analysis using metagenomics. He has a PhD from Carnegie Mellon University (2011), where he worked on bioimage informatics for subcellular location analysis with Bob Murphy. He is interested in combining meta'omics (methods that obtain high-throughput information on microbial communities such as metagenomics and metatranscriptomics) analysis with machine learning approaches to learn about microbial communities in different environments.

Willi Richert has a PhD in machine learning/robotics, where he used reinforcement learning, hidden Markov models, and Bayesian networks to let heterogeneous robots learn by imitation. Currently, he works for Microsoft in the Core Relevance Team of Bing, where he is involved in a variety of ML areas such as active learning, statistical machine translation, and growing decision trees.

Book Categories

Computer Science
15
Introduction to Computer Science
32
Introduction to Computer Programming
52
Algorithms and Data Structures
25
Artificial Intelligence
24
Computer Vision
30
Machine Learning
6
Neural Networks
22
Game Development and Multimedia
25
Data Communication and Networks
5
Coding Theory
16
Computer Security
9
Information Security
35
Cryptography
3
Information Theory
17
Computer Organization and Architecture
22
Operating Systems
2
Image Processing
11
Parallel Computing
4
Concurrent Programming
24
Relational Database
3
Document-oriented Database
14
Data Mining
16
Big Data
17
Data Science
23
Digital Libraries
22
Compiler Design and Construction
26
Functional Programming
11
Logic Programming
26
Object Oriented Programming
21
Formal Methods
70
Software Engineering
3
Agile Software Development
7
Information Systems
5
Geographic Information System (GIS)

Mathematics
67
Mathematics
14
Algebra
1
Abstract Algebra
27
Linear Algebra
3
Number Theory
8
Numerical Methods
2
Precalculus
10
Calculus
3
Differential Equations
5
Category Theory
11
Proofs
19
Discrete Mathematics
24
Theory of Computation
14
Graph Theory
2
Real Analysis
1
Complex Analysis
15
Probability
47
Statistics
7
Game Theory
5
Queueing Theory
13
Operations Research
16
Computer Aided Mathematics

Supporting Fields
21
Web Design and Development
1
Mobile App Design and Development
28
System Administration
2
Cloud Computing
10
Electric Circuits
6
Embedded System
28
Signal Processing
4
Network Science
3
Project Management

Operating System
Programming/Scripting
6
Ada
13
Assembly
34
C / C++
8
Common Lisp
2
Forth
35
Java
13
JavaScript
1
Lua
15
Microsoft .NET
1
Rexx
12
Perl
6
PHP
68
Python
12
R
1
Rebol
13
Ruby
2
Scheme
3
Tcl/Tk

Miscellaneous