Algorithms Archives - Page 31 of 31

OReilly – Working with Algorithms in Python (2014) [23 mp4]

21/06/2015 Learning for Life Leave a Comment

OReilly – Working with Algorithms in Python (2014) [23 mp4]
English | Size: 4.53 GB (4,861,614,367 bytes )
Category: Tutorial

Learn how to make your Python code more efficient by using algorithms to solve a variety of tasks or computational problems. In this video course, you’ll learn algorithm basics and then tackle a series of problems-such as determining the shortest path through a graph and the minimum edit distance between two genomic sequences-using existing algorithms.

Coursera – Stanford – Algorithms, Design and Analysis, Part 2 [104 Webrips (mp4)]

03/06/2015 Learning for Life Leave a Comment

Coursera – Stanford – Algorithms, Design and Analysis, Part 2 [104 Webrips (mp4)]
English | Size: 1.60 GB (1,720,984,198 bytes)
Category: Theory / Reference / Doc

In this course you will learn several fundamental principles of advanced algorithm design. You’ll learn the greedy algorithm design paradigm, with applications to computing good network backbones (i.e., spanning trees) and good codes for data compression. You’ll learn the tricky yet widely applicable dynamic programming algorithm design paradigm, with applications to routing in the Internet and sequencing genome fragments. You’ll learn what NP-completeness and the famous “P vs. NP” problem mean for the algorithm designer. Finally, we’ll study several strategies for dealing with hard (i.e., NP-complete problems), including the design and analysis of heuristics. Learn how shortest-path algorithms from the 1950s (i.e., pre-ARPANET!) govern the way that your Internet traffic gets routed today; why efficient algorithms are fundamental to modern genomics; and how to make a million bucks in prize money by “just” solving a math problem!
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Coursera – Stanford – Algorithms, Design and Analysis, Part 1 [82 Webrips (mp4)]

03/06/2015 Learning for Life Leave a Comment

Coursera – Stanford – Algorithms, Design and Analysis, Part 1 [82 Webrips (mp4)]
English | Size: 1.34 GB (1,439,999,036 bytes)
Category: Theory / Reference / Doc

In this course you will learn several fundamental principles of algorithm design. You’ll learn the divide-and-conquer design paradigm, with applications to fast sorting, searching, and multiplication. You’ll learn several blazingly fast primitives for computing on graphs, such as how to compute connectivity information and shortest paths. Finally, we’ll study how allowing the computer to “flip coins” can lead to elegant and practical algorithms and data structures. Learn the answers to questions such as: How do data structures like heaps, hash tables, bloom filters, and balanced search trees actually work, anyway? How come QuickSort runs so fast? What can graph algorithms tell us about the structure of the Web and social networks? Did my 3rd-grade teacher explain only a suboptimal algorithm for multiplying two numbers?
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Pluralsight Algorithms and Data Structures – Part 1

11/02/2015 Learning for Life Leave a Comment

Pluralsight Algorithms and Data Structures – Part 1
English | Size: 462.34 MB (484,802,828 Bytes)
Category: Tutorial

In this course we will look at the core data structures and algorithms used in everyday applications. We will discuss the trade-offs involved with choosing each data structure, along with traversal, retrieval, and update algorithms. This is part 1 of a two-part series of courses covering algorithms and data structures. In this part we cover linked lists, stacks, queues, binary trees, and hash tables.
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Pluralsight – Algorithms and Data Structures – Part 1

05/10/2014 Learning for Life Leave a Comment

Pluralsight – Algorithms and Data Structures – Part 1
English | Size: 328.62 MB
Category:CBTs

Working with Algorithms in Python

26/09/2014 Learning for Life Leave a Comment

Working with Algorithms in Python
English | Size: 4.53 GB
Category: CBTs

Description

Learn how to make your Python code more efficient by using algorithms to solve a variety of tasks or computational problems. In this video course, you’ll learn algorithm basics and then tackle a series of problems—such as determining the shortest path through a graph and the minimum edit distance between two genomic sequences—using existing algorithms.
[Read more…]