How Google Interferes With Its Search Algorithms and Changes Your R...
▻https://diasp.eu/p/9990444
How Google Interferes With Its Search Algorithms and Changes Your Results | #algorithms #google #search
How Google Interferes With Its Search Algorithms and Changes Your R...
▻https://diasp.eu/p/9990444
How Google Interferes With Its Search Algorithms and Changes Your Results | #algorithms #google #search
« What’s cooking? Part 4: Similarities » by Mark Needham, 23.04.2019
►https://medium.com/neo4j/whats-cooking-part-4-similarities-d4443d89556a #neo4j #graphs #algorithms #recipes
How to use the Jaccard Similarity Algorithm to compute recipe to recipe similarities, and more. Part 4 of the BBC Good Food Series.
The future of ethical tech education is open (▻https://opensource.co...
▻https://diasp.eu/p/9191188
The future of ethical tech education is open | #algorithms #ethics #opensource
How I got Rejected by 30+ Startups Before Landing a “Dream” Job
▻https://hackernoon.com/how-i-got-rejected-by-30-startups-before-landing-a-dream-job-6582e42aca7
I recently went through a job change and would like to post my experience. My post got a lot of people interested on reddit.TL;DR: Lot of companies do not focus on good engineering. Prepare. The algorithm rounds were a hit-or-miss for me.Always negotiate.Some facts:I resigned and decided to take a 2 month break to completely focus on job-huntingInterviewed (i.e. at least 1 online round) with 35+ companies. Mostly startups (seed to series A).Mostly in India. ~10 in EU, Japan, and other overseas countries through stack overflow careers. I don’t think my then 8k SO reputation helped out.I had linked to my medium profile in my CV and in 3 or 4 interviews (after initial screening rounds), we talked about my (somewhat controversial) blog Can’t hack your way to the topI practiced mostly using (...)
#interview #job-rejection #startup-job-rejection #startup-rejection #algorithms
Meet Max — The Algorithmic #crypto #wallet & Monitoring Service
▻https://hackernoon.com/meet-max-the-algorithmic-crypto-wallet-monitoring-service-9e76112f5989?s
Meet Max — The Algorithmic Crypto Wallet & Monitoring ServiceMore Than a Digital PocketJust so you’re aware, this is my very first time using Max. I’m logged into my portal right now but have yet to click on any of the Dropil project’s algorithmic products.I typically evaluate a product in advance before sharing its details but thought it’d be fun to have a fresh take, so this one’s meant to be a first-impression experience.I do however know that Max is one of four bots put together by the Dropil team. Max is the smart wallet that can stash proceeds harvested from arbitraging Arthur, or one of two virtual traders — Jade (currently in waitlist mode) and Dex 3.Speaking of Dex, that virtual, autopilot algo is why I’m writing this article in the first place. I spent 45 days — which equates to 3 (...)
Life Imitates Art Imitates the Algorithm
▻https://hackernoon.com/life-imitates-art-imitates-the-algorithm-d495637a41?source=rss----3a8144
Thoughts on Decentralization and what a Centralized Future Might HoldA History of CentralizationThe internet is like a country broken into several kingdoms. It started as a large pool of tribes and rag-tag communities, but a few parties realized what was being generated by these figurative villages. At which point they either intentionally or unintentionally took control of that resource: data.It’s happened throughout history, the larger and more organized communities realized they could gain resources and power by acquiring new territories. So they did. History is a bloody tapestry of conquests, crusades, and wars fought over whatever the flavor of the century was in terms of resources. Land, silk, salt, gold, there’re plenty of reasons to pillage. The same thing has been happening over (...)
#algorithm-life #algorithms #algorithm-art #art-imitates-algorithm #life-imitates-algorithm
Kadane’s Algorithm Explained
▻https://hackernoon.com/kadanes-algorithm-explained-50316f4fd8a6?source=rss----3a8144eabfe3---4
Given an array, the algorithm to find the maximum subarray sum is called Kadane’s Algorithm.The array can be of any dimension. For simplicity, let’s start with a 1D array.Let’s take a 0-indexed array:arr: [5, 7, -3, 2, 9, 6, 16, 22, 21, 29, -14, 10, 12]We can start the subarray at any point. Let’s say we start at index 2 i.e., arr[2] = -3. Now, at index 3, the sum will be -3 + 2 = -1. If we started the subarray at index 3 instead, the sum at index 3 is 2, which is greater than the previous sum.So we have two choices: either start at the current index or add the current element to the previous sum.And since we want the maximum subarray sum, we add the current element to the maximum of 0 and previous sum (zero here denotes that we’re starting anew from the current element).This problem falls (...)
Staying Relevant in the Age of AI: An Alibaba Guide for Algorithm Engineers
▻https://hackernoon.com/staying-relevant-in-the-age-of-ai-an-alibaba-guide-for-algorithm-enginee
As AI becomes adept in a growing range of computing tasks, the people working to develop it could soon find themselves out of a job.As artificial intelligence enters more and more of today’s technologies, aspiring algorithm engineers face a unique dilemma. On the one hand, they must compete to be qualified enough in AI to have development prospects; on the other, they risk becoming obsolete at the hands of the same AI models they are competing to work on.AI today has become such a popular field among developers that those returning to class reunions who have not pursued it risk becoming the butt of their classmates’ jokes. Far from being the new masters of an increasingly automated world, though, algorithm engineers are among those whose work could soon be replaced by the same development (...)
#algorithms #artificial-intelligence #human-development #software-engineering #programming
E=MC² for #diamonds: Creating universal access to the diamond industry with open-sourced #algorithms…
▻https://hackernoon.com/e-mc%C2%B2-for-diamonds-creating-universal-access-to-the-diamond-industr
E=MC² for Diamonds: Creating universal access to the diamond industry with open-sourced algorithms and self-sovereign identityKeeping too many secrets and a lack of good math has held the investment diamonds business back for centuries, until nowValuing investment diamonds is not easy… and the experts obviously don’t want you to know the price either.Canaries in a diamond mine — Recent efforts in the path to diamond fungibility has been an accumulation of counter-party risk, often causing centralized efforts to fall short and consistently missing basic features of a financial product. Some of these initiatives include basket vehicles and funds, slightly easier matching-trading interface or narrow specifications of the underlying for “futures” trading, yet diamond experts still mutually agree (...)
Using a multivariable linear regression model to predict the sprint speed of players in FIFA 19
▻https://hackernoon.com/using-a-multivariable-linear-regression-model-to-predict-the-sprint-spee
Using a multivariate linear regression model to predict the sprint speed of players in FIFA 19FIFA 19 Source: Express.co.ukI play FIFA games occasionally but classify myself as a relatively strong player who wins more often than not against other casual players. I am not a huge soccer fan in general and do not try and play a strategic game. Instead I rely heavily on player sprint speed and making unpredictable runs and turns. I often combine these skills to find and make spaces in my opponents space and dribble my way to a victory - much to the frustration of my opponent. Given this backdrop, I decided to download the FIFA19 dataset from Kaggle with the intention of predicting player sprint speed based on variables/features that I believed would best predict a player’s sprint (...)
#python #algorithms #machine-learning #data-science #linear-regression
Implementing Quicksort in #javascript
▻https://hackernoon.com/implementing-quicksort-in-javascript-45cb83ab1aa0?source=rss----3a8144ea
Quicksort is one of the most efficient methods for sorting an array in computer science. For a thorough breakdown, it has its own Wikipedia article.This article will cover implementing quicksort in JavaScript. Quicksort is not built in to JavaScript. Due to the sort method on the Array prototype, sorting is rarely questioned or optimized in the language. Despite that, Quicksort is still an important algorithm to at least comprehend, whether or not you use it.How does it work? ?Quicksort works by picking an element from the array and denoting it as the “pivot.” All other elements in the array are split into two categories — they are either less than or greater than this pivot element.Each of the two resulting arrays (array of values less-than-the-pivot and array of values (...)
Does business care about algorithmic skills?
▻https://hackernoon.com/does-business-care-about-algorithmic-skills-1ca7f42e2a03?source=rss----3
Do businesses care about algorithmic skills?Algorithms are a common question in every #interview. They became so widespread, that nobody even thinks about a reason for asking them. Every developer has to know how to solve random HackerRank task. Many companies believe it is the default requirement, so candidates do. But are you sure it’s a must-have skill for maintaining projects and meeting deadlines? I would say, it’s the most useless for these goals.TL;DR — I do not know how to solve algorithmic tasks, I don’t want to have that skill and I believe that mobile developers should ignore vacancies that require it.I had twenty interviews over the past year. Not all of them were successful. Typical examples of failed interviews:There were four steps of an interview in one company: knowledge of (...)
Sudokus and Schedules
▻https://hackernoon.com/sudokus-and-schedules-4b4693b07c2b?source=rss----3a8144eabfe3---4
Solving Scheduling Problems with Tree SearchPan Am’s Reservation Center in the 1950’sMachine learning is quite the rage these days, so much it is easy to lose sight of the fact there are other #algorithms in the “AI” space. As a matter of fact, these algorithms can be so crucial that it can be neglectful to overlook them.▻https://medium.com/media/5cdb4af8e1b955a096783fc3814f3114/hrefImagine you needed to schedule classes and classrooms. There are 36 periods, 36 rooms, and 800 lectures as your dimensions to schedule against. Want to take a guess how many possible configurations there are? Here is the answer: 1⁰²⁴⁹⁰ possible configurations. To put it in perspective, there are 1⁰⁸⁰ observable atoms in the universe. Even a task as mundane as classroom scheduling deals with astronomical numbers and (...)
#sudokus-and-schedules #machine-learning #artificial-intelligence #kotlin
Understanding binary #search
▻https://hackernoon.com/understanding-binary-search-e82d7bcbc06f?source=rss----3a8144eabfe3---4
Suppose, numbers is a list/array of integers that are sorted in nondecreasing order. We need to determine whether an element x is present in the list or not. There are n elements in the list .Linear searchBefore using binary search let’s check how linear search will perform in this problem.Let’s, n = 10⁶ ( here,numbers is a list of 10⁶ integers).If x is present at the first position of the list then we will get our expected result at the first iteration. This will work in O(1) time. Pretty fast! NO?But if x is present at 10⁶th position(or not present in the list) then it will take O(n) time to calculate the result and if we search for n times then time complexity will be O(n²), pretty slow, NO?So we can say that, at worst case linear search will work in O(n²) time complexity (for n number of (...)
Machine Learning #notes 2
▻https://hackernoon.com/machine-learning-notes-2-c0fe5a841c54?source=rss----3a8144eabfe3---4
From Machine Learning -Tom M. MitchellMachine Learning is at the forefront of advancements in Artificial Intelligence. It’s moving fast with new research coming out each and every day. This post is in continuation of important concepts and notes right from the basics to advance, from the book Machine Learning, by Tom M. Mitchell.For Machine Learning Notes 1, please click the link below.Machine Learning Notes 1CHAPTER 2: CONCEPT LEARNING AND THE GENERAL-TO-SPECIFIC ORDERING2.1 Concept LearningA problem of searching through a predefined space of potential hypothesis for the hypothesis that best fits the training example.Inferring a boolean-valued function from training examples of its input and output.Inductive Learning HypothesisAny hypothesis found to approximate the target function well (...)
Superalgos, Part One: The #trading Singularity
▻https://hackernoon.com/superalgos-part-one-the-trading-singularity-6f66f419982f?source=rss----3
Superalgos, Part One: The Trading SingularityOne day in the future, a trading intelligence capable of outperforming every other entity at the markets will emerge. Both humans and current #algorithms will be surpassed by Superalgos.By Luis Molina & Julian MolinaImage © GarryKillian, Shutterstock.AI is a hot topic these days.Elon Musk is still worried about the risks of a Technological Singularity happening as a result of advances in AI.You know, that moment in time when an Artificial Intelligence starts improving itself 24/7, non-stop, producing an exponential growth of intelligence that — in a short period of time — would render the most clever people on earth stupid.Such worries, of course, are justified…We know what happens when a species becomes so much more intelligent: the rest end up in (...)
#algorithmic-trading #cryptocurrency #artificial-intelligence
Binary Search In Detail
▻https://hackernoon.com/binary-search-in-detail-914944a1434a?source=rss----3a8144eabfe3---4
I hope we all have some idea about what binary search is and does. But I’m not going to explain the algorithm step by step, rather I’m going to give an insight into how binary search works and can be used.Check out: geeksforgeeks.org/binary-search if you’re unaware of Binary Search.Given a sorted array, we find the middle-most element and check the element with the key. If the middle-most element is equal to key, we’ve found the key. If the middle-most element is greater than the key, we search on the left half of the middle-most element, else we search on the right half.Here’s an iterative code for Binary Search in Java▻https://medium.com/media/da762279033b5bea50f5497a0df94f81/hrefNotice that in line 6, we useint mid = (low + high) / 2;But calculating mid this way is ineffective. Why? Let’s (...)
#binary-search #programming #java #binary-search-details #algorithms
Exploring Distributed System Theory: Availability and Consistency
▻https://hackernoon.com/exploring-distributed-system-theory-availability-and-consistency-e8c59e0
A senior Alibaba technical expert introduces the #algorithms that overcome limits proposed in the CAP theoremIn distributed systems, availability and consistency are the most basic prevailing issues, for which reason their relationship has been the subject of extensive study. The well-known CAP theorem defines their relationship as mutually exclusive in large-scale distributed environments, where the third factor in such systems, partition tolerance, cannot be treated as a variable. In an attempt to circumvent these issues, the Turing-award winning Paxos Protocol has since been proposed to maximize the efficiency of availability and consistency in such systems. To further address issues prevalent in this the Paxos algorithm, the ZAB Protocol was subsequently developed from an original (...)
#distributed-systems #software-development #high-availability #distributed-system-theory
String Reversal in #javascript
▻https://hackernoon.com/string-reversal-in-javascript-22651e20578d?source=rss----3a8144eabfe3---
Photo by Fancycrave on UnsplashString reversal is a very common interview question, and luckily it’s quite simple. There are many different ways to do this, but here are four methods, starting from the simplest and going to the most complex.Use arraysThis is a very straightforward method that leverages existing language features in order to accomplish a task. Most interviewers would ask you to perform the same task in a more ‘manual’ way if you tried this, but it demonstrates an awareness of Javascript, and is what I’d use in real life to accomplish this.Javascript allows you to call the reverse method on arrays. You can see some examples in the documentation here.So we would create a function that does the following:Converts the string to an arrayReverses the arrayTransforms the array back (...)
Sundar Pichai and The #ethics Of #algorithms
▻https://hackernoon.com/sundar-pichai-and-the-ethics-of-algorithms-7948226aa7f6?source=rss----3a
Today The Country Is Mocking Politicians, They Should Also Be Criticizing #google’s CEOPhoto by Goran Ivos on UnsplashThe latest congressional technology hearing was as cringeworthy as you would expect.There were politicians who thought Google was the same company as Apple. There were politicians that wondered why Google was censoring hate-speech. There were politicians that thought Sundar Pichai’s salary and some aggressive alpha-male shouting would enable him to reveal the answer to the age old mystery of “is Google tracking our every step?”Confused? So am I.▻https://medium.com/media/58608e2d554e15682f2d4b0e332d5c9c/hrefThrough all the hardships, Pichai remained calm and collected. He provided insight to a group of politicians who clearly lacked expertise. This is difficult to do and I give (...)
Tackle #bias and Other Problems/Solutions in Machine Learning Models
▻https://hackernoon.com/tackle-bias-and-other-problems-solutions-in-machine-learning-models-f427
Predictive Analytics models rely heavily on Regression, Classification and Clustering methods. When analysing the effectiveness of a predictive model, the closer the predictions are to the actual data, the better it is. This article hopes to be a one-stop reference to the major problems and their most popular/effective solutions, without diving into details for execution.A Linear Regression PlotA clustering algorithm plotPrimarily, data selection and pruning happens during the Data Preparation phase, where you take care to get rid of bad data in the first place. Then again, there are issues with the data, and their relevance to the ML model’s objectives during training, troubles with usage of #algorithms, and errors in the data that occur throughout. Effectively, the model is tested for (...)
#machine-learning #machine-learning-models #predictive-analytics
Basic Introduction to All #google #algorithms
▻https://hackernoon.com/basic-introduction-to-all-google-algorithms-539389f96f15?source=rss----3
You might have heard of the term “Algorithm” before, it is a process or set of rules used in calculations and problem-solving operations.Today, we will get an overview of different Google Algorithms that have transformed the search experience for us.Google’s mission statement is to organize the world’s information and make it universally accessible and useful.To achieve its mission, Google implements changes in its formula or the algorithm. Many changes are pushed by Google in a year, some are small improvements in their current algorithms and some just turns the industry upside down.So let’s take a look at all the important algorithms –1. Google PandaGoogle Panda was released by Google on February 24, 2011, and is used to detect duplicate, plagiarized content and excessive use of keywords.The (...)
#algorithms and Data Structures #interview Preparison & Questions — Part 1
▻https://hackernoon.com/algorithms-and-data-structures-interview-preparison-questions-part-1-a23
Algorithms and Data Structures Interview Preparation & Walkthrough — Part 1Finding the first job for a new grad (Source: Sparks Group)Many of new graduates want to knock on the doors of big companies in Silicon Valley such as Facebook, Amazon, Apple, Netflix, Google and Microsoft. However, preparing for a technical interview is a long and tiresome process. I, myself is also a SW engineer, been there, done that, but still, at some days I will need to face the process again. So I decided to write some articles to remind myself (and you) to get through the process as smooth as possible.Useful ResourcesAlgorithms, Part 1 and Algorithms, Part 2 are two of the most famous free online courses for Algorithms in case you want to refresh your memory.There are two other books I would recommend (...)
#algorithms and Data Structures #interview Preparation & Walkthrough — Part 2, Array and String
▻https://hackernoon.com/algorithms-and-data-structures-interview-preparation-walkthrough-part-2-
Algorithms and Data Structures Interview Preparation & Walkthrough — Part 2, Array and StringArrrrr…. Ray!(Source: Gorgaiphotography/iStock)In my previous post: Algorithms and Data Structures Interview Preparation & Walkthrough — Part 1, we talked about how to do Complexity Time and Space analysis, and also see the common Big-O factors with examples.In this post, I will start talking about Array in depth, and cover some interview questions and hopefully by the end of the reading, you would have a good glance about Array. Once we are familiar with Array, I will talk about String and how to use Array to solve String problems.Array is a data structure that contains a group of elements. The most basic implementation of an array is a static array. The reason it’s called static is the size (...)
A Difference Between DL and #statistics
▻https://hackernoon.com/a-difference-between-dl-and-statistics-c3939b999f75?source=rss----3a8144
Photo by Robert Anasch on UnsplashOne thing that I love about being in grad school is the unending innovation that reverberates in the corridors. Sure, I sit in a cubicle part-time coding my life away, but there are moments where people step out of their hole to converse with those around them.One of these structured ways is through the weekly update meetings, and one of the many conversations we have inspired this post.Let’s start off with statistics.One of statistics’ main focus is to create a generalizable model, such as a linear or multivariate regression model, to best fit the data to represent the pattern you are investigating.There are other key topics in statistics like statistical significance, correlation vs. causation, probability theory, and model evaluation that are shared (...)
#deep-learning #machine-learning #algorithms #dl-and-statistics