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دانلود کتاب Dive Into Algorithms

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Dive Into Algorithms

مشخصات کتاب

Dive Into Algorithms

ویرایش: [1 ed.] 
نویسندگان:   
سری:  
ISBN (شابک) : 9781718500693, 1718500688 
ناشر: No Starch Press 
سال نشر: 2021 
تعداد صفحات: 248 
زبان: English 
فرمت فایل : EPUB (درصورت درخواست کاربر به PDF، EPUB یا AZW3 تبدیل می شود) 
حجم فایل: 5 Mb 

قیمت کتاب (تومان) : 39,000



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Dive Into Algorithms is a wide-ranging, Pythonic tour of many of the world's most interesting algorithms. With little more than a bit of computer programming experience and basic high-school math, you'll explore standard computer science algorithms for searching, sorting, and optimization; human-based algorithms that help us determine how to catch a baseball or eat the right amount at a buffet; and advanced algorithms like ones used in machine learning and artificial intelligence. You'll even explore how ancient Egyptians and Russian peasants used algorithms to multiply numbers, how the ancient Greeks used them to find greatest common divisors, and how Japanese scholars in the age of samurai designed algorithms capable of generating magic squares. You'll explore algorithms that are useful in pure mathematics and learn how mathematical ideas can improve algorithms. You'll learn about an algorithm for generating continued fractions, one for quick calculations of square roots, and another for generating seemingly random sets of numbers. You'll also learn how to: - Use algorithms to debug code, maximize revenue, schedule tasks, and create decision trees - Measure the efficiency and speed of algorithms - Generate Voronoi diagrams for use in various geometric applications - Use algorithms to build a simple chatbot, win at board games, or solve sudoku puzzles - Write code for gradient ascent and descent algorithms that can find the maxima and minima of functions - Use simulated annealing to perform global optimization - Build a decision tree to predict happiness based on a person's characteristics Once you've finished this book you'll understand how to code and implement important algorithms as well as how to measure and optimize their performance, all while learning the nitty-gritty details of today's most powerful algorithms.



فهرست مطالب

Contents in Detail
Acknowledgments
Introduction
	Who Is This Book For?
		About This Book
		Setting Up the Environment
			Install Python on Windows
			Install Python on macOS
			Install Python on Linux
			Installing Third-Party Modules
		Summary
Chapter 1: Problem-Solving With Algorithms
	The Analytic Approach
		The Galilean Model
		The Solve-for-x Strategy
		The Inner Physicist
	The Algorithmic Approach
		Thinking with Your Neck
		Applying Chapman’s Algorithm
		Solving Problems with Algorithms
	Summary
Chapter 2: Algorithms in History
	Russian Peasant Multiplication
		Doing RPM by Hand
		Implementing RPM in Python
	Euclid’s Algorithm
		Doing Euclid’s Algorithm by Hand
		Implementing Euclid’s Algorithm in Python
	Japanese Magic Squares
		Creating the Luo Shu Square in Python
		Implementing Kurushima\'s Algorithm in Python
	Summary
Chapter 3: Maximizing and Minimizing
	Setting Tax Rates
		Steps in the Right Direction
		Turning the Steps into an Algorithm
	Objections to Gradient Ascent
	The Problem of Local Extrema
		Education and Lifetime Income
		Climbing the Education Hill—the Right Way
	From Maximization to Minimization
	Hill Climbing in General
	When Not to Use an Algorithm
	Summary
Chapter 4: Sorting and Searching
	Insertion Sort
		Putting the Insertion in Insertion Sort
		Sorting via Insertion
	Measuring Algorithm Efficiency
		Why Aim for Efficiency?
		Measuring Time Precisely
		Counting Steps
		Comparing to Well-Known Functions
		Adding Even More Theoretical Precision
		Using Big O Notation
	Merge Sort
		Merging
		From Merging to Sorting
	Sleep Sort
	From Sorting to Searching
		Binary Search
		Applications of Binary Search
	Summary
Chapter 5: Pure Math
	Continued Fractions
		Compressing and Communicating Phi
		More about Continued Fractions
		An Algorithm for Generating Continued Fractions
		From Decimals to Continued Fractions
		From Fractions to Radicals
	Square Roots
		The Babylonian Algorithm
		Square Roots in Python
	Random Number Generators
		The Possibility of Randomness
		Linear Congruential Generators
		Judging a PRNG
		The Diehard Tests for Randomness
		Linear Feedback Shift Registers
	Summary
Chapter 6: Advanced Optimization
	Life of a Salesman
		Setting Up the Problem
		Brains vs. Brawn
		The Nearest Neighbor Algorithm
		Implementing Nearest Neighbor Search
		Checking for Further Improvements
		Algorithms for the Avaricious
		Introducing the Temperature Function
	Simulated Annealing
		Tuning Our Algorithm
		Avoiding Major Setbacks
		Allowing Resets
		Testing Our Performance
	Summary
Chapter 7: Geometry
	The Postmaster Problem
	Triangles 101
	Advanced Graduate-Level Triangle Studies
		Finding the Circumcenter
		Increasing Our Plotting Capabilities
	Delaunay Triangulation
		Incrementally Generating Delaunay Triangulations
		Implementing Delaunay Triangulations
	From Delaunay to Voronoi
	Summary
Chapter 8: Language
	Why Language Algorithms Are Hard
	Space Insertion
		Defining a Word List and Finding Words
		Dealing with Compound Words
		Checking Between Existing Spaces for Potential Words
		Using an Imported Corpus to Check for Valid Words
		Finding First and Second Halves of Potential Words
	Phrase Completion
		Tokenizing and Getting N-grams
		Our Strategy
		Finding Candidate n + 1-grams
		Selecting a Phrase Based on Frequency
	Summary
Chapter 9: Machine Learning
	Decision Trees
	Building a Decision Tree
		Downloading Our Dataset
		Looking at the Data
		Splitting Our Data
		Smarter Splitting
		Choosing Splitting Variables
		Adding Depth
	Evaluating Our Decision Tree
		The Problem of Overfitting
		Improvements and Refinements
	Random Forests
	Summary
Chapter 10: Artificial Intelligence
	La Pipopipette
	Drawing the Board
	Representing Games
	Scoring Games
	Game Trees and How to Win a Game
		Building Our Tree
		Winning a Game
		Adding Enhancements
	Summary
Chapter 11: Forging Ahead
	Doing More with Algorithms
	Building a Chatbot
		Text Vectorization
		Vector Similarity
	Becoming Better and Faster
	Algorithms for the Ambitious
	Solving the Deepest Mysteries
Index




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