Read "Streaming Systems" 1&2, Streaming 101 Read "F1, a distributed SQL database that scales" Read "Zanzibar, Google’s Consistent, Global Authorization System" Read "Spanner, Google's Globally-Distributed Database" Read "Designing Data-intensive applications" 12, The Future of Data Systems IOS development with Swift Read "Designing Data-intensive applications" 10&11, Batch and Stream Processing Read "Designing Data-intensive applications" 9, Consistency and Consensus Read "Designing Data-intensive applications" 8, Distributed System Troubles Read "Designing Data-intensive applications" 7, Transactions Read "Designing Data-intensive applications" 6, Partitioning Read "Designing Data-intensive applications" 5, Replication Read "Designing Data-intensive applications" 3&4, Storage, Retrieval, Encoding Read "Designing Data-intensive applications" 1&2, Foundation of Data Systems Three cases of binary search TAMU Operating System 2 Memory Management TAMU Operating System 1 Introduction Overview in cloud computing 2 TAMU Operating System 7 Virtualization TAMU Operating System 6 File System TAMU Operating System 5 I/O and Disk Management TAMU Operating System 4 Synchronization TAMU Operating System 3 Concurrency and Threading TAMU Computer Networks 5 Data Link Layer TAMU Computer Networks 4 Network Layer TAMU Computer Networks 3 Transport Layer TAMU Computer Networks 2 Application Layer TAMU Computer Networks 1 Introduction Overview in distributed systems and cloud computing 1 A well-optimized Union-Find implementation, in Java A heap implementation supporting deletion TAMU Advanced Algorithms 3, Maximum Bandwidth Path (Dijkstra, MST, Linear) TAMU Advanced Algorithms 2, B+ tree and Segment Intersection TAMU Advanced Algorithms 1, BST, 2-3 Tree and Heap TAMU AI, Searching problems Factorization Machine and Field-aware Factorization Machine for CTR prediction TAMU Neural Network 10 Information-Theoretic Models TAMU Neural Network 9 Principal Component Analysis TAMU Neural Network 8 Neurodynamics TAMU Neural Network 7 Self-Organizing Maps TAMU Neural Network 6 Deep Learning Overview TAMU Neural Network 5 Radial-Basis Function Networks TAMU Neural Network 4 Multi-Layer Perceptrons TAMU Neural Network 3 Single-Layer Perceptrons Princeton Algorithms P1W6 Hash Tables & Symbol Table Applications Stanford ML 11 Application Example Photo OCR Stanford ML 10 Large Scale Machine Learning Stanford ML 9 Anomaly Detection and Recommender Systems Stanford ML 8 Clustering & Principal Component Analysis Princeton Algorithms P1W5 Balanced Search Trees TAMU Neural Network 2 Learning Processes TAMU Neural Network 1 Introduction Stanford ML 7 Support Vector Machine Stanford ML 6 Evaluate Algorithms Princeton Algorithms P1W4 Priority Queues and Symbol Tables Stanford ML 5 Neural Networks Learning Princeton Algorithms P1W3 Mergesort and Quicksort Stanford ML 4 Neural Networks Basics Princeton Algorithms P1W2 Stack and Queue, Basic Sorts Stanford ML 3 Classification Problems Stanford ML 2 Multivariate Regression and Normal Equation Princeton Algorithms P1W1 Union and Find Stanford ML 1 Introduction and Parameter Learning

Ruby practice 4

2016-05-02

Q1: Palindromes

Adapt your solution from the “palindromes” question so that instead of writing palindrome?(“foo”)you can write “foo”.palindrome?

My Example Code

# add new method to String class
class String
	def palindrome?()
		s = self.downcase.gsub(/\W*/,"")
		s == s.reverse
	end
end

# or we can use method_missing
class String
	def method_missing(m,*args,&block)
		# m is method name(a symbol), use id2name or to_s
		# self is foo in this case
		if m.id2name == "palindrome?"
			s = self.downcase.gsub(/\W/,"")
			s == s.reverse 
		else
			# if no match here, retrun to ancestor
			super
		end
	end
end

puts "foo".palindrome? # => false
word = "foof"
puts word.palindrome? # =>true

Q2: Enumerable Palindrome

Adapt your palindrome solution so that it works on Enumerables. That is:
[1,2,3,2,1].palindrome? # => true

(It is not necessary for the collection’s elements to be palindromes themselves - only that the top-level collection be a palindrome.) Although hashes are considered Enumerables, your solution does not need to make sense for hashes (though it should not produce an error).

My Example Code

module Enumerable
	def palindrome?
		if self.kind_of?(Array)
			self == self.reverse
		else
			temp = self.to_a
			temp == temp.reverse
		end
	end
end

a = [1,2,[1,2],2,1]
b = [["a"],"b","b",["a"]]
puts a.palindrome?
puts b.palindrome?

Q3: Cartesian Product (use yield)

Given two collections (of possibly different lengths), we want to get the Cartesian product of the sequence - in other words, every possible pair of N elements where one element is drawn from each collection.
For example, the Cartesian product of the sequences a=[:a,:b,:c] and b=[4,5] is: a×b = [[:a,4],[:a,5],[:b,4],[:b,5],[:c,4],[:c,5]]

Create a method that accepts two sequences and returns an iterator that will yield the elements of the Cartesian product, one at a time, as a two-element array.

  1. It doesn’t matter what order the elements are returned in. So for the above example, the ordering [[:a,4], [:b,4], [:c,4], [:a,5], [:b,5], [:c,5]] would be correct, as would any other ordering.
  2. It does matter that within each pair, the order of the elements matches the order in which the original sequences were provided. That is, [:a,4] is a member of the Cartesian product a×b, but [4,:a] is not. (Although [4,:a] is a member of the Cartesian product b×a.)

To start you off, here is a pastebin link to skeleton code (http://pastebin.com/cgSuhtPf) showing possible correct results. For your convenience the code is also shown below

class CartesianProduct
    include Enumerable
        # your code here
    end
# Examples of use
c = CartesianProduct.new([:a,:b], [4,5])
c.each { |elt| puts elt.inspect }
# [:a, 4]
# [:a, 5]
# [:b, 4]
# [:b, 5]
c = CartesianProduct.new([:a,:b], [])
c.each { |elt| puts elt.inspect }
# (nothing printed since Cartesian product
# of anything with an empty collection is empty)

My Example Code

class CartesianProduct
	include Enumerable
	def initialize(arr_1,arr_2)
		@arr_1 = arr_1
		@arr_2 = arr_2
	end
		
	def each()
		if block_given?
			len1, len2 = @arr_1.size, @arr_2.size
			(0...len1).each do |i|
				(0...len2).each do |j|
					element = [@arr_1[i],@arr_2[j]]
					yield element
				end
			end
		else
			return "Blcok missing!"
		end
	end	
end

c = CartesianProduct.new([:a,:b,:c], [4,5])
c.each {|elt| puts elt.inspect}
puts c.each 

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