MakCorps - Hotel Price Comparison API

Design inspired by the Cognitive Bias Codex View the high resolution version of the infographic by clicking here . Out of all the interventions we can do to make smarter decisions in our life and career, mastering the most useful and universal mental models is arguably the most important. Over the last few months, I’ve written about how many of the most successful self-made billionaire entrepreneurs like Ray Dalio , Elon Musk , and Charlie Munger swear by mental models… “Developing the habit of mastering the multiple models which underlie reality is the best thing you can do. “ — Charlie Munger “Those who understand more of them and understand them well [principles / mental models] know how to interact with the world more effectively than those who know fewer of them or know them less well. “ — Ray Dalio “It is important to view knowledge as sort of a semantic tree — make sure you understand the fundamental principles, i.e. the trunk and big branches, bef

MakCorps — Hotel Price Comparison API have a separate team of expert developers who are seasoned professional when it comes to API consumption and integration. Whether it’s a travel and hospitality API or a payment gateway API or a Social Media APIs (Facebook, Twitter, Google+ etc.), they are thoroughly experienced. What is MakCorps Hotel Price Comparison API MakCorps Hotels API is a Hotel price comparison API which compares more than 200 Hotel websites to generate JSON response with top 6 vendors. Our aim is to create a transparent panel for your customers so that they can book their dream hotels in a very cheap price. MakCorps Advance version response MakCorps XML/JSON API enables a distinct sorted hotels with low prices from multiple API suppliers and wholesalers.. MakCorps API enables Online Travel Agencies (OTAs), Metasearch and Travel Management Companies (TMCs) and Corporate companies to search, book and manage relevant hotel content. How long does t

Node.js can be intimidating to beginners. But its flexible structure and lack of strict guidelines makes it seem more complicated than it is. This tutorial is a quick and simple guide to Node.js, the Express framework, and MongoDB, focusing on the fundamental REST routes and basic database interaction. You’ll build a simple API boilerplate that can then be used as the foundation for any app. Who This Tutorial Is For : You should have a basic understanding of REST APIs and CRUD operations, plus basic JavaScript knowledge. I use ES6 (mainly fat-arrow functions), but nothing too complex. For this tutorial, you’ll create the skeleton of a back-end for a note-taking application — think Google Keep . You want to be able to do all four CRUD actions on your notes: create, read, update, and delete. Setting Up If you don’t have Node installed, see here . In a new directory, run npm init, and follow along with the prompts, giving your app the name of ‘notable’ (or whateve

Artificial Intelligence (AI) is the mantra of the current era. The phrase is intoned by technologists, academicians, journalists and venture capitalists alike. As with many phrases that cross over from technical academic fields into general circulation, there is significant misunderstanding accompanying the use of the phrase. But this is not the classical case of the public not understanding the scientists — here the scientists are often as befuddled as the public. The idea that our era is somehow seeing the emergence of an intelligence in silicon that rivals our own entertains all of us — enthralling us and frightening us in equal measure. And, unfortunately, it distracts us. There is a different narrative that one can tell about the current era. Consider the following story, which involves humans, computers, data and life-or-death decisions, but where the focus is something other than intelligence-in-silicon fantasies. When my spouse was pregnant 14 years ago, we h

Simple explanations of Artificial Intelligence, Machine Learning, and Deep Learning and how they’re all different. Plus, how AI and IoT are inextricably connected. We’re all familiar with the term “Artificial Intelligence.” After all, it’s been a popular focus in movies such as The Terminator, The Matrix, and Ex Machina (a personal favorite of mine). But you may have recently been hearing about other terms like “Machine Learning” and “Deep Learning,” sometimes used interchangeably with artificial intelligence. As a result, the difference between artificial intelligence, machine learning, and deep learning can be very unclear. I’ll begin by giving a quick explanation of what Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) actually mean and how they’re different. Then, I’ll share how AI and the Internet of Things are inextricably intertwined, with several technological advances all converging at once to set the foundation for an AI and

Training your model is hands down the most time consuming and expensive part of machine learning. Training your model on a GPU can give you speed gains close to 40x, taking 2 days and turning it into a few hours. However, this normally comes at a cost to your wallet. The other day I stumbled upon a great tool called Google Colab. I would describe Colab as the google docs equivalent of Jupyter notebooks. Colab is aimed at being an education and research tool for collaborating on machine learning projects. The great part is, that it’s completely free forever . There is no setup to use it. I didn’t even need to log in. (I was already logged into my google account) The best part is that you get an unlimited supply of 12 hours of continuous access to a k80 GPU, which is pretty powerful stuff. (You get disconnected after 12 hours, but you can use it as many times as you want) I want our focus to be training on a GPU and Colab specific so the notebook is extremely bare bon