book

Python One-Liners

by Christian Mayer

April 2020

Intermediate to advanced

216 pages

5h 19m

English

No Starch Press

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Python One-Liner ExampleA Note on ReadabilityWho Is This Book For?What Will You Learn?Online Resources

Basic Data StructuresContainer Data StructuresControl FlowFunctionsLambdasSummary
Using List Comprehension to Find Top EarnersUsing List Comprehension to Find Words with High Information ValueReading a FileUsing Lambda and Map FunctionsUsing Slicing to Extract Matching Substring EnvironmentsCombining List Comprehension and SlicingUsing Slice Assignment to Correct Corrupted ListsAnalyzing Cardiac Health Data with List ConcatenationUsing Generator Expressions to Find Companies That Pay Below Minimum WageFormatting Databases with the zip() FunctionSummary
Basic Two-Dimensional Array ArithmeticWorking with NumPy Arrays: Slicing, Broadcasting, and Array TypesConditional Array Search, Filtering, and Broadcasting to Detect OutliersBoolean Indexing to Filter Two-Dimensional ArraysBroadcasting, Slice Assignment, and Reshaping to Clean Every i-th Array ElementWhen to Use the sort() Function and When to Use the argsort() Function in NumPyHow to Use Lambda Functions and Boolean Indexing to Filter ArraysHow to Create Advanced Array Filters with Statistics, Math, and LogicSimple Association Analysis: People Who Bought X Also Bought YIntermediate Association Analysis to Find Bestseller BundlesSummary
The Basics of Supervised Machine LearningLinear RegressionLogistic Regression in One LineK-Means Clustering in One LineK-Nearest Neighbors in One LineNeural Network Analysis in One LineDecision-Tree Learning in One LineGet Row with Minimal Variance in One LineBasic Statistics in One LineClassification with Support-Vector Machines in One LineClassification with Random Forests in One LineSummary
Finding Basic Textual Patterns in StringsWriting Your First Web Scraper with Regular ExpressionsAnalyzing Hyperlinks of HTML DocumentsExtracting Dollars from a StringFinding Nonsecure HTTP URLsValidating the Time Format of User Input, Part 1Validating Time Format of User Input, Part 2Duplicate Detection in StringsDetecting Word RepetitionsModifying Regex Patterns in a Multiline StringSummary
Finding Anagrams with Lambda Functions and SortingFinding Palindromes with Lambda Functions and Negative SlicingCounting Permutations with Recursive Factorial FunctionsFinding the Levenshtein DistanceCalculating the Powerset by Using Functional ProgrammingCaesar’s Cipher Encryption Using Advanced Indexing and List ComprehensionFinding Prime Numbers with the Sieve of EratosthenesCalculating the Fibonacci Series with the reduce() FunctionA Recursive Binary Search AlgorithmA Recursive Quicksort AlgorithmSummary

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4MACHINE LEARNING

Machine learning is found in almost every area of computer science. Over the past few years, I’ve attended computer science conferences in fields as diverse as distributed systems, databases, and stream processing, and no matter where I go, machine learning is already there. At some conferences, more than half of the presented research ideas have relied on machine learning methods.

As a computer scientist, you must know the fundamental machine learning ideas and algorithms to round out your overall skill set. This chapter provides an introduction to the most important machine learning algorithms and methods, and gives you 10 ...