Udemy – Data Structure and Algorithms Analysis – Job Interview

Udemy – Data Structure and Algorithms Analysis – Job Interview
English | Size: 0.99 GB
Category: Tutorial

This course prepared depending on my real job interviews experiences with Google, Microsoft, Amazon, and Snapchat.In this course you will learn how to Analysis algorithms like Sorting, Searching, and Graph algorithms. And how to reduce the code complexity from one Big-O level to another level. Furthermore, you will learn different type of Data Structure for your code. Also you will learn how to find Big-O for every data structure, and how to apply correct Data Structure to your problem in Java. By the end you will be able to write code that run faster and use low memory. You Also will learn how to analysis problems using Dynamic programming. We will discus code complexity in Different algorithms like Sorting algorithms ( Bubble, Merge, Heap, and quick sort) , searching algorithms ( Binary search, linear search, and Interpolation), Graph algorithms( Binary tree, DFS, BFS, Nearest Neighbor and Shortest path, Dijkstra’s Algorithm, and A* Algorithm). and Data Structure like Dynamic Array, Linked List, Stack, Queue, and Hash-Table [Read more…]

Udemy – Introduction to Algorithms and Data structures in C++

Udemy – Introduction to Algorithms and Data structures in C++
English | Size: 476.72 MB
Category: Programming

"I learned a lot of thingsfrom this course. The GOLD trick was awesome."Arpan P.

"I started thinking about problems in a more efficient way…" Mokshagna S.

"It’s deep, rich in information, consistent and dense" Laurentiu M.

"It’s a very good course, it focuses on building your concept." Saransh S.

"Awesome, it’s just awesome"Yazan R.
[Read more…]

Udemy – The Coding Interview Bootcamp Algorithms Data Structures

Udemy – The Coding Interview Bootcamp Algorithms Data Structures
English | Size: 1.76 GB
Category: CBTs

What Will I Learn?
Master commonly asked interview questions
Tackle common data structures used in web development
Practice dozens of different challenges
Use Javascript to solve challenging algorithms
Requirements
Basic understanding of Javascript
Description
Data Structures? They’re here. Algorithms? Covered. Lots of questions with well-explained solutions? Yep!
[Read more…]

The Coding Interview Bootcamp Algorithms + Data Structures [Udemy] (2017)

The Coding Interview Bootcamp: Algorithms + Data Structures [Udemy] (2017)
English | Size: 1.76 GB
Category: Tutorial

What Will I Learn?

Master commonly asked interview questions
Tackle common data structures used in web development
Practice dozens of different challenges
Use Javascript to solve challenging algorithms

Data Structures? They’re here. Algorithms? Covered. Lots of questions with well-explained solutions? Yep!

If you’re nervous about your first coding interview, or anxious about applying to your next job, this is the course for you. I got tired of interviewers asking tricky questions that can only be answered if you’ve seen the problem before, so I made this course! This video course will teach you the most common interview questions that you’ll see in a coding interview, giving you the tools you need to ace your next whiteboard interview. [Read more…]

Ed Finn – What Algorithms Want – (23 mp3s)

Ed Finn – What Algorithms Want – (23 mp3s)
English | Size: 246.66 MB
Category: Audio

We depend on – we believe in – algorithms to help us get a ride, choose which book to buy, execute a mathematical proof. It’s as if we think of code as a magic spell, an incantation to reveal what we need to know and even what we want. Humans have always believed that certain invocations – the marriage vow, the shaman’s curse – do not merely describe the world but make it. Computation casts a cultural shadow that is shaped by this long tradition of magical thinking. In What Algorithms Want, Ed Finn considers how the algorithm – in practical terms, "a method for solving a problem" – has its roots not only in mathematical logic but also in cybernetics, philosophy, and magical thinking. [Read more…]

Packt Publishing – Extending Machine Learning Algorithms

Packt Publishing – Extending Machine Learning Algorithms
English | Size: 398.28 MB
Category: Tutorial

Complex statistics in Machine Learning worry a lot of developers. Knowing statistics helps you build strong Machine Learning models that are optimized for a given problem statement. Understand the real-world examples that discuss the statistical side of Machine Learning and familiarize yourself with it. We will use libraries such as scikit-learn, e1071, randomForest, c50, xgboost, and so on.We will discuss the application of frequently used algorithms on various domain problems, using both Python and R programming.It focuses on the various tree-based machine learning models used by industry practitioners.We will also discuss k-nearest neighbors, Naive Bayes, Support Vector Machine and recommendation engine.By the end of the course, you will have mastered the required statistics for Machine Learning Algorithm and will be able to apply your new skills to any sort of industry problem. [Read more…]

Learning C Sharp Algorithms

Learning C Sharp Algorithms
English | Size: 235.36 MB
Category: CBTs

Understanding algorithms is a key requirement for all programmers. Algorithms give programs a set of instructions to perform a task. Expand your knowledge of common C# algorithms for sorting, searching, sequencing, and more. Learn how to apply them to optimize your C# developer skills and answer crucial interview questions. Reynald Adolphe reviews linked lists, stacks, queues, and binary and linear search. [Read more…]

O’Reilly – Supervised Classification Algorithms

O’Reilly – Supervised Classification Algorithms
English | Size: 497.49 MB
Category: Tutorial

Classification is the sub-field of machine learning encountered more frequently than any other in data science applications. There are many different classification techniques and this course explains some of the most important ones, including algorithms such as logistic regression, k-nearest neighbors (k-NN), decision trees, ensemble models like random forests, and support vector machines. The course also covers Naive Bayes classifiers and in so doing, covers Bayes’ theorem and basic Bayesian inference, both of which are widely used in training many machine learning algorithms. A basic knowledge of algebra is required. A solid understanding of differential calculus will be necessary for logistic regression, Support Vector Machines and Bayesian Inference. [Read more…]

Packt Publishing – Advanced Functional Data Structures and Algorithms

Packt Publishing – Advanced Functional Data Structures and Algorithms
English | Size: 732.69 MB
Category: Tutorial

Algorithms and datastructures are fundamentals in computer programming. Functional data structures have the power to improve the codebase of an application and improve its efficiency. With the advent of functional programming and powerful functional languages such as Scala, Clojure, and Elixir becoming part of important enterprise applications, functional data structures have gained an important place in the developer toolkit.
[Read more…]

Udemy – Learning Algorithms in JavaScript from Scratch – QIJKI

Udemy – Learning Algorithms in JavaScript from Scratch – QIJKI
English | Size: 389.68 MB
Category: Tutorial

This course teaches algorithms in javascript from the ground up. Using algorithms in your programming allows you to improve the efficiency, performance, speed, and scalability of your code/applications/programs. You will learn what algorithms are, why they are important, and how to code them out in JavaScript. You will also learn other important programming concepts along the way such as functional programming, time complexity, recursion, and other important concepts, because you will be implementing them in the algorithms that you build throughout this course. This course also heavily uses diagrams and animations to help make understanding the material easier. [Read more…]