NumPy Beginner’s Guide (2nd Edition) by Ivan Idris

By Ivan Idris

NumPy is an extension to, and the elemental package deal for clinical computing with Python. In today's international of technological know-how and know-how, it's all approximately velocity and suppleness. in terms of clinical computing, NumPy is at the best of the list.

NumPy Beginner's consultant will educate you approximately NumPy, a number one medical computing library. NumPy replaces many of the performance of Matlab and Mathematica, yet not like these items, is loose and open source.

Write readable, effective, and quick code, that's as with regards to the language of arithmetic as is at present attainable with the innovative open resource NumPy software program library. research all of the fine details of NumPy that calls for you to understand uncomplicated Python purely. retailer hundreds of thousands of bucks on pricey software program, whereas conserving the entire flexibility and gear of your favorite programming language.You will find out about fitting and utilizing NumPy and similar techniques. on the finish of the booklet we are going to discover a few similar medical computing tasks. This e-book offers you a superb beginning in NumPy arrays and common features. via examples, additionally, you will know about plotting with Matplotlib and the comparable SciPy undertaking. NumPy Beginner's consultant might help you be efficient with NumPy and feature you writing fresh and speedy code very quickly at all.

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Natural Language Processing: Python and NLTK by Nitin Hardeniya, Jacob Perkins, Deepti Chopra, Nisheeth

By Nitin Hardeniya, Jacob Perkins, Deepti Chopra, Nisheeth Joshi, Iti Mathur

Learn to construct professional NLP and laptop studying tasks utilizing NLTK and different Python libraries

About This Book

  • Break textual content down into its part elements for spelling correction, characteristic extraction, and word transformation
  • Work via NLP ideas with easy and easy-to-follow programming recipes
  • Gain insights into the present and budding study themes of NLP

Who This e-book Is For

If you're an NLP or computing device studying fanatic and an intermediate Python programmer who desires to speedy grasp NLTK for traditional language processing, then this studying course will do you many of excellent. scholars of linguistics and semantic/sentiment research pros will locate it invaluable.

What you are going to Learn

  • The scope of ordinary language complexity and the way they're processed through machines
  • Clean and wrangle textual content utilizing tokenization and chunking that will help you approach info better
  • Tokenize textual content into sentences and sentences into words
  • Classify textual content and practice sentiment analysis
  • Implement string matching algorithms and normalization techniques
  • Understand and enforce the techniques of knowledge retrieval and textual content summarization
  • Find out how you can enforce quite a few NLP initiatives in Python

In Detail

Natural Language Processing is a box of computational linguistics and synthetic intelligence that offers with human-computer interplay. It presents a continuing interplay among pcs and humans and provides pcs the power to appreciate human speech with the aid of desktop studying. The variety of human-computer interplay situations are expanding so it truly is turning into central that desktops understand all significant traditional languages.

The first NLTK necessities module is an advent on how you can construct structures round NLP, with a spotlight on find out how to create a personalized tokenizer and parser from scratch. you are going to study crucial suggestions of NLP, receive sensible perception into open resource instrument and libraries on hand in Python, proven the right way to examine social media websites, and receive instruments to accommodate huge scale textual content. This module additionally presents a workaround utilizing many of the impressive features of Python libraries comparable to NLTK, scikit-learn, pandas, and NumPy.

The moment Python three textual content Processing with NLTK three Cookbook module teaches you the fundamental concepts of textual content and language processing with basic, simple examples. This contains organizing textual content corpora, developing your individual customized corpus, textual content class with a spotlight on sentiment research, and allotted textual content processing equipment.

The 3rd studying usual Language Processing with Python module can assist you turn into a professional and help you in growing your personal NLP initiatives utilizing NLTK. you may be guided via version improvement with computer studying instruments, proven the way to create education info, and given perception into the simplest practices for designing and development NLP-based functions utilizing Python.

This studying course combines the very best that Packt has to supply in a single whole, curated package deal and is designed that will help you speedy examine textual content processing with Python and NLTK. It comprises content material from the subsequent Packt products:

  • NTLK necessities through Nitin Hardeniya
  • Python three textual content Processing with NLTK three Cookbook through Jacob Perkins
  • Mastering traditional Language Processing with Python via Deepti Chopra, Nisheeth Joshi, and Iti Mathur

Style and approach

This entire direction creates a gentle studying direction that teaches you ways to start with common Language Processing utilizing Python and NLTK. you will learn how to create potent NLP and laptop studying tasks utilizing Python and NLTK.

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Python Data Visualization Cookbook (2nd Edition) by Igor Milovanovic, Dimitry Foures, Giuseppe Vettigli

By Igor Milovanovic, Dimitry Foures, Giuseppe Vettigli

Over 70 recipes to get you all started with well known Python libraries in response to the crucial options of information visualization

About This Book
Learn tips on how to organize an optimum Python setting for info visualization
Understand find out how to import, fresh and manage your data
Determine varied techniques to info visualization and the way to decide on the main acceptable in your needs
Who This publication Is For
If you realize approximately Python programming and need to appreciate info, facts codecs, facts visualization, and the way to take advantage of Python to imagine information then this booklet is for you.

What you are going to Learn
Introduce your self to the fundamental tooling to establish your operating environment
Explore your information utilizing the functions of normal Python info Library and Panda Library
Draw your first chart and customise it
Use the most well-liked info visualization Python libraries
Make 3D visualizations commonly utilizing mplot3d
Create charts with pictures and maps
Understand the main acceptable charts to explain your data
Know the matplotlib hidden gems
Use to proportion your visualization online

In Detail
Python facts Visualization Cookbook will development the reader from the purpose of putting in and developing a Python setting for facts manipulation and visualization all of the approach to 3D animations utilizing Python libraries. Readers will reap the benefits of over 60 targeted and reproducible recipes that would consultant the reader in the direction of a greater knowing of information techniques and the development blocks for next and occasionally extra complex concepts.
Python info Visualization Cookbook begins through displaying find out how to organize matplotlib and the similar libraries which are required for many components of the publication, earlier than relocating directly to talk about a few of the lesser-used diagrams and charts equivalent to Gantt Charts or Sankey diagrams. firstly it makes use of basic plots and charts to extra complicated ones, to make it effortless to appreciate for readers. because the readers will battle through the ebook, they'll get to understand concerning the 3D diagrams and animations. Maps are irreplaceable for showing geo-spatial info, so this publication also will convey the right way to construct them. within the final bankruptcy, it comprises rationalization on the way to contain matplotlib into diversified environments, resembling a writing process, LaTeX, or the right way to create Gantt charts utilizing Python.

Style and approach
A step by step recipe dependent method of facts visualization. the subjects are defined sequentially as cookbook recipes along with a code snippet and the ensuing visualization.

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Python pocket reference by Lutz M.

By Lutz M.

This is often the e-book to arrive for if you find yourself coding at the fly and wish a solution now. it really is an easy-to-use connection with the center language, with descriptions of generic modules and toolkits, and a advisor to contemporary alterations, new positive aspects, and upgraded built-ins -- all up to date to hide Python 3.X in addition to model 2.6. you are going to additionally quick locate precisely what you would like with the convenient index.Written by way of Mark Lutz -- well known because the world's top Python coach -- Python Pocket Reference, Fourth version, is definitely the right significant other to O'Reilly's vintage Python tutorials, additionally written via Mark: studying Python and Programming Python. integrated item forms, together with numbers, lists, dictionaries, and extra Statements and syntax for developing and processing items features and modules for structuring and reusing code Python's object-oriented programming instruments The exception-handling version integrated features, exceptions, and attributes unique operator overloading tools commonly used regular library modules and extensions Command-line ideas and improvement instruments Python idioms and tricks

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High Performance Python: Practical Performant Programming by Micha Gorelick, Ian Ozsvald

By Micha Gorelick, Ian Ozsvald

Your Python code may possibly run safely, yet you would like it to run swifter. by way of exploring the basic idea at the back of layout offerings, this functional advisor is helping you achieve a deeper figuring out of Python's implementation. You'll the way to find functionality bottlenecks and considerably accelerate your code in high-data-volume programs.

How are you able to make the most of multi-core architectures or clusters? Or construct a approach which could scale up and down with out wasting reliability? skilled Python programmers will study concrete options to those and different concerns, in addition to warfare tales from businesses that use excessive functionality Python for social media analytics, productionized laptop studying, and different situations.

-Get a greater seize of numpy, Cython, and profilers
-Learn how Python abstracts the underlying desktop architecture
-Use profiling to discover bottlenecks in CPU time and reminiscence usage
-Write effective courses by means of selecting acceptable information structures
-Speed up matrix and vector computations
-Use instruments to assemble Python all the way down to computing device code
-Manage a number of I/O and computational operations concurrently
-Convert multiprocessing code to run on an area or distant cluster
-Solve huge difficulties whereas utilizing much less RAM

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Think Stats by Allen Downey B.

By Allen Downey B.

If you know the way to application, you might have the talents to show info into wisdom utilizing the instruments of likelihood and records. This concise advent indicates you ways to accomplish statistical research computationally, instead of mathematically, with courses written in Python.

You'll paintings with a case research in the course of the publication that will help you examine the complete information research process—from amassing facts and producing records to picking out styles and trying out hypotheses. alongside the best way, you'll get to grips with distributions, the foundations of chance, visualization, and plenty of different instruments and concepts.
* advance your figuring out of likelihood and records by means of writing and checking out code
* Run experiments to check statistical habit, equivalent to producing samples from a number of distributions
* Use simulations to appreciate recommendations which are difficult to know mathematically
* examine issues no longer often coated in an introductory path, equivalent to Bayesian estimation
* Import information from nearly any resource utilizing Python, instead of be restricted to facts that has been wiped clean and formatted for statistics instruments
* Use statistical inference to reply to questions about real-world info

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Introduction to Tornado: Modern Web Applications with Python by Michael Dory

By Michael Dory

Stroll in the course of the fundamentals of twister, the high-performance internet server identified for its pace, simplicity, and scalability on tasks huge and small. With this hands-on consultant, you are going to use Tornado's acclaimed positive aspects via operating with numerous instance functions. you furthermore mght get most sensible practices for utilizing twister within the actual international. Are you curious about making a scalable social program, real-time analytics engine, or RESTful API - all with the ability and ease of Python? This ebook exhibits you why twister is astounding selection for writing strong purposes which are uncomplicated to create, expand, and install.

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Data Structures and Algorithms Using Python by Rance D. Necaise

By Rance D. Necaise

Все больше и больше программистов обращаются к языку Python, и эта книга даст им понимание того, что им нужно. Автор представляет основную структуру массива и исследует основы реализации и использовании многомерных массивов. Изложены основные механизмы, многие структуры и конструкции из встроенных даннёых языка Python. Чтобы понять, как вводятся новые структуры данных Число АТД и приложений, рассматриваются как потоки на протяжении всей книги,. Также представлены реальные приложения. Это дает программистам полный охват основных структур данных и алгоритмов в языке Python.
More and extra programmers are turning to Python and this e-book will provide them the certainty they wish. Necaise introduces the fundamental array constitution and explores the basics of imposing and utilizing multi-dimensional arrays. The underlying mechanisms of a lot of Python’s integrated info buildings and constructs are coated. a couple of ADTs and functions are mentioned as threads during the ebook to permit for a number of implementations as new information constructions are brought. Real-world functions of many of the bankruptcy subject matters also are provided. this offers programmers entire assurance of abstraction and the fundamental information constructions and algorithms within the Python language.
This publication is designed for an information constructions and algorithms direction that makes use of Python. A key target is to supply a «back to fundamentals» method of studying information constructions and algorithms with out overwhelming the reader with the entire object-oriented programming terminology and ideas. to supply flexibility in subject assurance for a large choice of classes, the writer specializes in information buildings and algorithms, whereas designing the examples to permit the creation of object-oriented programming if that is so wanted. The ebook additionally introduces the idea that of set of rules research and explores the potency of algorithms and information constructions through the text.
Provides entire insurance of abstraction and the elemental info buildings and algorithms utilizing a «back to fundamentals» approach.
Python (version three) used to layout and enforce periods for summary info forms and courses and algorithms.
Flexible organziation permits insurance of sophistication inheritance as wanted or desired.
Introduces scholars to the elemental array constitution and the basics of imposing and utilizing multi-dimensional arrays.
The underlying mechanism of a lot of Pythons integrated facts constructions and constructs are explored in an effort to disclose the «magic» and to judge their efficiency.
Sample purposes of assorted bankruptcy subject matters are awarded during the textual content to assist have interaction students.
A variety of ADTs and purposes are awarded as threads through the textual content (i.e. the Set, Bag, Matrix, Sparse Matrix, and Map ADTs.) this permits for a number of implementations as new information buildings are brought, which supplies the chance to enhance the abstraction proposal and for learning set of rules efficiency.

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