[pyar] [ANN] Libro: Learning scikit-learn: Machine Learning in Python

[Gustavo Orrillo]

gracias por el aviso! ya lo compré! :) Muy pero muy interesante que haya
gente por aca que este usando scikit para tareas de Machine Learning


On Thu, Nov 28, 2013 at 2:07 PM, Elvio Rogelio Toccalino <
elviotoccalino en gmail.com> wrote:

> Gracias por el aviso. Casualmente lo estaba leyendo :)
>
>
> 2013/11/28 Nicolas Bases <nmbases en gmail.com>
>
>> Gracias!
>>
>>
>> 2013/11/28 Elias <copybin en gmail.com>
>>
>>>
>>> Hace poquito acaba de publicarse el libro:
>>> *Learning scikit-learn: Machine Learning in Python*
>>> ya está disponible en Amazon: http://amzn.com/1783281936
>>> Autores: Raúl Garreta, Guillermo Moncecchi
>>>
>>> Ambos de la comunidad python de Uruguay :D,
>>>
>>> Saludos, Elías
>>>
>>> ----------------------------
>>>
>>> Experience the benefits of machine learning techniques by applying them
>>> to real-world problems using Python and the open source scikit-learn library
>>>
>>> *Overview*
>>>
>>>    - Use Python and scikit-learn to create intelligent applications
>>>    - Apply regression techniques to predict future behaviour and learn
>>>    to cluster items in groups by their similarities
>>>    - Make use of classification techniques to perform image recognition
>>>    and document classification
>>>
>>> *In Detail*
>>>
>>> Machine learning, the art of creating applications that learn from
>>> experience and data, has been around for many years. However, in the era of
>>> “big data”, huge amounts of information is being generated. This makes
>>> machine learning an unavoidable source of new data-based approximations for
>>> problem solving.
>>>
>>> With Learning scikit-learn: Machine Learning in Python, you will learn
>>> to incorporate machine learning in your applications. The book combines an
>>> introduction to some of the main concepts and methods in machine learning
>>> with practical, hands-on examples of real-world problems. Ranging from
>>> handwritten digit recognition to document classification, examples are
>>> solved step by step using Scikit-learn and Python.
>>>
>>> The book starts with a brief introduction to the core concepts of
>>> machine learning with a simple example. Then, using real-world applications
>>> and advanced features, it takes a deep dive into the various machine
>>> learning techniques.
>>>
>>> You will learn to evaluate your results and apply advanced techniques
>>> for preprocessing data. You will also be able to select the best set of
>>> features and the best methods for each problem.
>>>
>>> With Learning scikit-learn: Machine Learning in Python you will learn
>>> how to use the Python programming language and the scikit-learn library to
>>> build applications that learn from experience, applying the main concepts
>>> and techniques of machine learning.
>>>
>>> *What you will learn from this book*
>>>
>>>    - Set up scikit-learn inside your Python environment
>>>    - Classify objects (from documents to human faces and flower
>>>    species) based on some of their features, using a variety of methods from
>>>    Support Vector Machines to Naïve Bayes
>>>    - Use Decision Trees to explain the main causes of certain
>>>    phenomenon such as the Titanic passengers’ survival
>>>    - Predict house prices using regression techniques
>>>    - Display and analyse groups in your data using dimensionality
>>>    reduction
>>>    - Make use of different tools to preprocess, extract, and select the
>>>    learning features
>>>    - Select the best parameters for your models using model selection
>>>    - Improve the way you build your models using parallelization
>>>    techniques
>>>
>>> *Approach*
>>>
>>> The book adopts a tutorial-based approach to introduce the user to
>>> Scikit-learn.
>>>
>>> *Who this book is written for*
>>>
>>> If you are a programmer who wants to explore machine learning and
>>> data-based methods to build intelligent applications and enhance your
>>> programming skills, this the book for you. No previous experience with
>>> machine-learning algorithms is required.
>>>
>>> _______________________________________________
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>>
>>
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>
>
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