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Showing posts with label Python ebooks. Show all posts
Showing posts with label Python ebooks. Show all posts

22 September, 2020

Working with Excel files in Python

Working with Excel files in Python
Clinton W. Brownley
"Learn python for data analysis” is a constant refrain for those looking to develop their data analysis skills. But it’s hard to apply beginning Python skills to your everyday work if the data you deal with is in Excel spreadsheets. This lesson gives you the ability to connect your new skills to the data you’re already working with, and gives you a big step up on the Python learning curve.

What you’ll learn—and how you can apply it

This lesson teaches you to ingest Excel spreadsheet files into Python scripts and begin to leverage Python’s powerful analysis and automation tools, using both base Python and pandas.

This lesson is for you because…

You deal with data in spreadsheets as part of your job and are beginning to learn Python; this chapter gives you the ability to start applying your Python knowledge right away.

Prerequisites

Beginning Python knowledge Familiarity with Excel Materials or downloads needed in advance 
Python 3.x
Year:
2018
Publisher:
O'Reilly Media, Inc.
Language:
english
File:
PDF, 3.03 MB
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19 September, 2020

Python Data Science

Python Data Science: The Ultimate Handbook for Beginners on How to Explore NumPy for Numerical Data, Pandas for Data Analysis, IPython, Scikit-Learn and Tensorflow for Machine Learning and Business
Steve Blair
Year:
2019
Publisher:
Steve Blair
Language:
english
Pages:
216
ISBN 10:
1081068000
File:
PDF, 1.90 MB
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17 September, 2020

Python One-Liners 2020

Python One-Liners 2020
Christian Mayer
Python programmers will improve their computer science skills with these useful one-liners.

Python One-Liners will teach you how to read and write "one-liners": concise statements of useful functionality packed into a single line of code. You'll learn how to systematically unpack and understand any line of Python code, and write eloquent, powerfully compressed Python like an expert.

The book's five chapters cover tips and tricks, regular expressions, machine learning, core data science topics, and useful algorithms. Detailed explanations of one-liners introduce key computer science concepts and boost your coding and analytical skills. You'll learn about advanced Python features such as list comprehension, slicing, lambda functions, regular expressions, map and reduce functions, and slice assignments. You'll also learn how to:

    Leverage data structures to solve real-world problems, like using Boolean indexing to find cities with above-average pollution
    Use NumPy basics such as array, shape, axis, type, broadcasting, advanced indexing, slicing, sorting, searching, aggregating, and statistics
    Calculate basic statistics of multidimensional data arrays and the K-Means algorithms for unsupervised learning
    Create more advanced regular expressions using grouping and named groups, negative lookaheads, escaped characters, whitespaces, character sets (and negative characters sets), and greedy/nongreedy operators
    Understand a wide range of computer science topics, including anagrams, palindromes, supersets, permutations, factorials, prime numbers, Fibonacci numbers, obfuscation, searching, and algorithmic sorting

By the end of the book, you'll know how to write Python at its most refined, and create concise, beautiful pieces of "Python art" in merely a single line.
Categories:
Computers\\Programming
Year:
2020
Publisher:
No Starch Press
Language:
english
Pages:
256
ISBN 10:
1718500505
ISBN 13:
9781718500501
File:
PDF, 3.36 MB
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16 September, 2020

[Free Course]Artificial Intelligence: Reinforcement Learning in Python ~ Google Driver 2020

15 September, 2020

Natural Language Processing Recipes: Unlocking Text Data with Machine Learning and Deep Learning using Python

Natural Language Processing Recipes: Unlocking Text Data with Machine Learning and Deep Learning using Python
Akshay KulkarniAdarsha Shivananda
Implement natural language processing applications with Python using a problem-solution approach. This book has numerous coding exercises that will help you to quickly deploy natural language processing techniques, such as text classification, parts of speech identification, topic modeling, text summarization, text generation, entity extraction, and sentiment analysis.
Natural Language Processing Recipes starts by offering solutions for cleaning and preprocessing text data and ways to analyze it with advanced algorithms. You’ll see practical applications of the semantic as well as syntactic analysis of text, as well as complex natural language processing approaches that involve text normalization, advanced preprocessing, POS tagging, and sentiment analysis. You will also learn various applications of machine learning and deep learning in natural language processing.
By using the recipes in this book, you will have a toolbox of solutions to apply to your own projects in the real world, making your development time quicker and more efficient.

What You Will Learn
• Apply NLP techniques using Python libraries such as NLTK, TextBlob, spaCy, Stanford CoreNLP, and many more
• Implement the concepts of information retrieval, text summarization, sentiment analysis, and other advanced natural language processing techniques.
• Identify machine learning and deep learning techniques for natural language processing and natural language generation problems

Who This Book Is For
Data scientists who want to refresh and learn various concepts of natural language processing through coding exercises.
Categories:
Computers\\Cybernetics: Artificial Intelligence
Year:
2019
Edition:
1
Publisher:
Apress
Language:
english
Pages:
234 / 253
ISBN 10:
1484242661
ISBN 13:
978-1484242667
File:
PDF, 3.82 MB
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