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Showing posts from 2018

Java For Android

While a number of languages can be used to build Android apps, Java is the language Google encourages developers to use. However, it's not precisely the same as the Java you may have encountered on other platforms. There are some subtle differences and peculiarities and it's important for you as an Android developer to get your head around them.



In this tutorial, you'll take a quick tour of Java in the Android world and find out more about the features it offers. Along the way you'll also learn:
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The .NET Core 2 Wave

I sat down with Scott Hunter (Director of Program Management for the .NET Platform) on the Eat Sleep Code podcast to talk about all things .NET. Scott shared plans for an exciting year of .NET development including the .NET Core 2 Wave, which includes the .NET Core 2.0 release along with .NET Standard 2.0, adoption strategies, and Visual Studio 2017 tooling.
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It’s a Good Day to Be a C# Developer

Recently at Connect(), Microsoft made a slew of new announcements. First, the public availability of Visual Studio 2017 Release Candidate. This just isn't a new version of the signature developer tool, it also includes the latest bits for C# 7.0. Second, Google announced they were joining the .NET Foundation. This means that Google, technically a competitor of Microsoft, wants to be actively involved in the evolution of .NET (and indirectly C#). Third, the first public release of Visual Studio for Mac. As a native environment, Visual Studio for Mac will provide the same world class tooling support for Xamarin applications, using C# and F#.
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Build and Deploy Your ASP.NET Core Application with Apache

ASP.NET Core is the latest web framework from Microsoft that supports development with C# and the .NET Framework. In this latest incarnation of ASP.NET, you can choose to use an alternative .NET framework called .NET Core in order to deliver on some amazing new promises from the Microsoft team. By using the .NET Core framework with ASP.NET Core, you can develop and publish your applications on non-Windows platforms like MacOS or Linux. In this article, we're going to review the steps you need to know in order to build and deploy to a Linux server running Apache.
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The New Configuration Model in ASP.NET Core

ASP.NET Core has a lot of changes compared with the others versions of ASP.NET. One change I want to highlight is the new way to configure settings. With previous versions, this configuration was made by using the common file web.config, but this file simply doesn't exist anymore in ASP.NET Core. Instead, a new easy way to declare and access to the settings is provided. Let's take a look.
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Telerik UI for UWP Now Open Source

We are happy to announce that Telerik UI for Universal Windows Platform by Progress is now free and open-source. Yes, you read that correctly! Telerik UI for UWP is now open sourced under the Apache Software License (ASLv2) and is available for download for FREE. The UI for UWP repo on GitHub is now available to the public.
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Importing 3D Models for ARKit

ARKit is the hot new technology in iOS 11 that lets you view and interact with virtual objects in real space.



It's not hard to get an ARKit project up and running, but getting your 3D art into it can present some challenges. Fortunately, once your art is imported, you can make a number of adjustments in Xcode's SceneKit Editor — SceneKit being the 3D graphics framework that ARKit employs.



We're going to look at preparing your art for ARKit, getting it into the SceneKit Editor, and making final adjustments. You will need an ARKit-capable iOS device to proceed. You won't get anything useful out of running an ARKit app on the Xcode simulator.
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Place Objects In Augmented Reality Via ARKit

Hello there! In this article, I will explain you how to place objects in augmented reality via ARKit.



If you haven't already, I recommend you to have a look at the initial article in which I give an in-depth introduction to ARKit and the possibilities of Augmented Reality in iOS.



Furthermore, if you are not proficient with detecting planes in augmented reality, I would suggest you to first have a look at the article on detecting planes in ARKit. This post will start from the latter. Thus, it's important that you understand the concepts behind Augmented Reality and Plane Detection.



Are you still with me? Good! Let's start then.



Oh, and as always, you can download the source code from my Github Repository.
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Augmented Reality With ARKit: Detecting Planes

In our previous article about Augmented Reality with ARKit, we learned the basics of the new augmented reality platform from Apple. In this post, we are going to continue our exploration of its possibilities by learning how detecting planes works, and how to visualize them in our applications. Let's start!



As always, you can get the full code from my Github repository.
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Build ARKit Application with Unity

Create a new Unity project(or use your existing one), search and import the Unity ARKit plugin in the asset store.



The plugin contains a handy tool ARKitRemote which allows us developing AR app purely in the editor(watch this video for more about it), it also includes lots of examples, please check them after you have an overview of how ARKit works.
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This art…

Building an AR app with ARKit and Scenekit

In the last tutorial, we used SpriteKit to create an augmented reality (AR) game with ARKit. Today, it's the turn of Scenekit.



Remember that SpriteKit works with 2D content while SceneKit works with 3D content. However, this brings its own problems.



How do I get a 3D model into Xcode?

What format do I use for the model?

How does touch handling works in a 3D space?

This tutorial will answer those questions and show you how to use ARKit with SceneKit by building the following app:
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ARKit Adventures - Making A Remote Control Drone

In the last few posts on ARKit, most of the content we placed was pretty static. For this example, I want to switch gears and make something in ARKit that is a bit more interactive.



If you've ever wanted to play around with a remote-controlled drone but have never had the opportunity to do so, this tutorial is for you. I know the controls look a bit stupid at the moment, but the point of this post isn't to create a genuinely impressive interface, it's to get you started down the road where you're interacting with the augmented world.
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ARKit by Example — Part 4: Realism - Lighting & PBR

In this article we are going to insert more realistic looking virtual content in to the scene. We can achieve this by using more detailed models using a technique called Physically Based Rendering (PBR) and also a more accurate representation of lighting in the scene.



To see the updates, check out the video below, instead of just plane solid boring cubes we now have added some PBR based materials that give us a much more realistic object that seems to fit into the real world, with variable lighting and reflections.
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ARKit by Example — Part 3: Adding geometry and physics fun

In the last article we used ARKit to detect horizontal planes in the real world, then visualized those planes. In this article we are now going to start adding virtual content to our AR experience and start interacting with the planes that were detected.



By the end of this article we will be able to drop cubes into the world, apply realistic physics to the cubes so they interact with one another and also create mini shock waves to make the cubes fly around a bit.



Here is a video showing the app in action, you can see how first we capture the horizontal planes, then we add some 3D cubes to interact with the scene and then finally cause some mini explosions to make the cubes jump around:
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ARKit By Example — Part 2: Plane Detection + Visualization

In our first hello world ARKit app we setup our project and rendered a single virtual 3D cube which would render in the real world and track as you moved around.



In this article, we will look at extracting 3D geometry from the real world and visualizing it. Detecting geometry is very important for Augmented Reality apps because if you want to be able to feel like you are interacting with the real world you need to know that the user clicked on a table top, or is looking at the floor, or another surface to get life-like 3D interactions. Once we have the plane detection completed in this article, in a future article we will use them to place virtual objects in the real world.



ARKit can detect horizontal planes (I suspect in the future ARKit will detect more complex 3D geometry but we will probably have to wait for a depth sensing camera for that, iPhone8 maybe…). Once we detect a plane, we will visualize it to show the scale and orientation of the plane. To see it all in action, watch t…

ARKit by Example — Part 1: AR Cube

This first article is going to create a really simple hello world AR app using ARKit. By the end we will be able to position a 3D cube inside the augmented world and move around it with our iOS device.



To render 3D content inside ARKit, we are going to use SceneKit: https://developer.apple.com/scenekit/ This is a framework for rendering 3D graphics on an iOS device. If you are familiar with basic 3D concepts it will be pretty straightforward.



If you can't wait until the end of the article, here is a video of the app in action. As you can see using ARKit we can place virtual objects in the real world and have them stick in place as we move the camera around.



Even though this is a very simple app, we will keep building more and more features through these series of articles, including geometry detection, 3D physics and lots more fun things.
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Augmented Reality With ARKit For IOS

This is a series of tutorials focused on Augmented Reality with ARKit. Alongside MLKit, this was the framework announcement that impressed me the most. I strongly believe that ARKit is going to be a game changer for the Augmented Reality ecosystem.







This initial tutorial will get you started with ARKit in iOS with examples and little to no theory. First, we will start with just some basic concepts. Then, we will learn how to load different types of model, from static object to animated figures, mainly using SceneKit. Also, I will show you how to import blender models into ARKit. By the end of this tutorial, you will be able to load and place virtual objects in the real world.



As always, you can download the full source code for the sample project from my Github repository.
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iOS ARKit Tutorial: Drawing in the Air with Bare Fingers

Recently, Apple announced its new augmented reality (AR) library named ARKit. For many, it looked like just another good AR library, not a technology disruptor to care about. However, if you take a look at AR progress in the past couple of years, one shouldn't be too quick to draw such conclusions.



Interacting with virtual objects in an iOS ARKit app



In this post, we will create a fun project using iOS ARKit. The user will place his fingers on a table as if they were holding a pen, tap on the thumbnail and start drawing. Once finished, the user will be able to transform their drawing into a 3D object, as shown in the animation below. The full source code for our iOS ARKit example is available at GitHub.
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Using ARKit with Metal

Augmented Reality provides a way of overlaying virtual content on top of real world views usually obtained from a mobile device camera. Last month at WWDC 2017 we were all thrilled to see Apple's new ARKit framework which is a high level API that works with A9-powered devices or newer, running on iOS 11. Some of the ARKit experiments we've already seen are outstanding, such as this one below:
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ARKit + Vision: An intriguing combination

After multiple weeks of pondering what I should do first with Apple's newly announced ARKit, I decided that I wouldn't narrow my mindset to just the one API. I had viewed multiple tutorials on CoreML/Vision's object recognition, and I decided to give it a shot myself.




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Building an AR game with ARKit and Spritekit

ARKit is the new Apple framework that integrates device motion tracking, camera capture, and scene processing to build augmented reality (AR) experiences.



When using ARKit, you have three options to create your AR world:



SceneKit, to render 3D overlay content

SpriteKit, to render 2D overlay content

Metal, to build your own view for an AR experience

In this tutorial, we're going to explore the basics of ARKit and SpriteKit by building a game, something inspired by Pokemon Go, but with ghosts, check out this video:
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ARKit introduction

Apple has announced at WWDC17 a new iOS framework called ARKit. It's a framework that "allows you to easily create unparalleled augmented reality experiences for iPhone and iPad". The framework is shipped with the iOS 11 (currently in beta) and it's only supported by iOS devices that are powered by Apple's A9 or A10 chip. This means that it won't be working on older devices like iPhone 5S or iPad Mini. In addition, you can't use it in the simulator so you have to update your iPhone/iPad with the latest beta (iOS 11 SDK is only available in Xcode 9).



AR - creating the illusion that virtual objects are placed in a physical world using a camera.



We know that Augmented Reality isn't new but AR is getting a lot of buzz right now because of the Apple's new framework. One of the first and probably the most famous app that showed us the power of AR in apps was Pokemon Go. Achieving apps with the same interactivity as Pokemon Go isn't easy and that'…

Android Developer Beginner. Step #2��� –  Creating Lists

In Android, we have two ways of implementing a list — ListView and RecyclerView. The first one is a good old UI component, which has been included in the Android SDK since the very beginning. I used it a lot of times when an app needed a scrolling list.



The RecyclerView, however, was announced with Android Lollipop. It's a kind of ListView2 but the name isn't accidental. RecyclerView introduces a few more components that we should use, but it's not a big deal – the responsibilities are split, so it's a good change.



Generally, it's better to use RecyclerView when it's possible. But to understand why it's worth doing this, we first need to implement lists using both ways. Let's start with ListView.



Both implementations are separated into different posts, as well as the final comparison of the two. Thanks to this, if you aren't interested in the ListView, you can jump straight to the RecyclerView without endless scrolling. However, I encourage you to r…

How to Create a Measuring App With ARKit In iOS 11

I'm sure that many of you (like me) were really excited when Apple announced a new framework – ARKit – at WWDC 2017. The demo was really interesting and most of us started wondering: what else can we achieve by using that framework? In this post, I would like to show you how to create a basic measuring app. That's correct – your device is able to measure things located in the real world! But, for now, let's start from the beginning.
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Getting started with ARKi

With WWDC's announcement of ARKit I knew I had to try out some of the new stuff they announced. I decided to play around with the new ARKit. I wanted to link it somehow with music so I decided to build a disco ball in augmented reality to enhance your boogie experience.
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Mastering MVVM on iOS

There are a plenty of posts on the internet about app architectures in the iOS development world. Today I will show some tips for using MVVM architecture while developing iOS apps. I am not going to show other architectures if you need them there is a great post (https://medium.com/ios-os-x-development/ios-architecture-patterns-ecba4c38de52 ).



Why MVVM?

The main problem of Apple MVC is mixed responsibility, which leads to the appearance of some kinds of problems such as Massive-View-Controller.



We should accept that UIViewController is the main component in Apple's iOS SDK and all the actions are started and built across this entity. Despite the name, it is more View than a Classic Controller (or Presenter) from MVC( or MVP), because of callbacks like viewDidLoad, viewWillLayoutSubviews, and other view related methods. That is the reason why we should ignore the Controller keyword in the name and use it as View, where the role of real Controller takes the ViewModel.




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https://medium.com/swlh/a-machine-learning-model-to-understand-fancy-abbreviations-trained-on-tolkien-36601b73ecbb

Recently I bumped into a question on Stackoverflow, how to recover phrases from abbreviations, e.g. turn "wtrbtl" into "water bottle", and "bsktball" into "basketball". The question had an additional complication: lack of comprehensive list of words. That means, we need an algorithm able to invent new likely words.



I was intrigued and started researching, which algorithms and math lie behind modern spell-checkers. It turned out that a good spell-checker can be made with an n-gram language model, a model of word distortions, and a greedy beam search algorithm. The whole construction is called a noisy channel model.



With this knowledge and Python, I wrote a model from scratch. After training on "The Fellowship of the Ring" text, it was able to recognize abbreviations of modern sports terms.



Spell checkers are widely used: from your phone's keyboard to search engines and voice assistants. It's not easy to make a good spell checker…

4 Must Have Skills Every Data Scientist Should Learn

We wanted to follow up our previous piece about how to grow as a data scientist with some other skills senior data scientists should have. Our hope is to bridge the gap between business managers and technical data scientists by creating clear goals senior data scientists can aim for. Both entities have to take on very different problems. Both benefit when they are on the same page. This is why the previous post focused so highly on communication. It seems simple, but the gap between technical and business continues to grow as new technologies keep getting piled on every year. Thus, we find it important that managers and data scientists have a clear path of expectations.
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10 Machine Learning Algorithms You need to Know

In machine learning, there's something called the "No Free Lunch" theorem. In a nutshell, it states that no one algorithm works best for every problem, and it's especially relevant for supervised learning (i.e. predictive modeling).



For example, you can't say that neural networks are always better than decision trees or vice-versa. There are many factors at play, such as the size and structure of your dataset.



As a result, you should try many different algorithms for your problem, while using a hold-out "test set" of data to evaluate performance and select the winner.



Of course, the algorithms you try must be appropriate for your problem, which is where picking the right machine learning task comes in. As an analogy, if you need to clean your house, you might use a vacuum, a broom, or a mop, but you wouldn't bust out a shovel and start digging.
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My Journey Into Data Science and Bio-Informatics — Part 1: Programming

According to IBM, 2.5 quintillion (10¹⁸) bytes of data, or 2.5 million terabytes, is being generated every day (an average computer holds 1 terabyte). 90 percent of all the data that exists, has been generated in the last two years. Furthermore, it's expected that this growth will keep on accelerating. This results in a bottleneck where the processing and interpretation of the data lags behind. And it's not only Twitter, Facebook, Google and Netflix that are faced with these problems. Biomedicine, biology, physics, pharma… are faced with this problem as well.



To illustrate the problem further, a single whole-genome sequencing can be multiple hundred gigabytes in size (exome and RNA is approx. 100 times smaller). It requires a specific set of skills to deal with such a large amount of data. That's where bio-informatics comes in
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Understanding Feature Engineering (Part 1) — Continuous Numeric Data

Any intelligent system basically consists of an end-to-end pipeline starting from ingesting raw data, leveraging data processing techniques to wrangle, process and engineer meaningful features and attributes from this data. Then we usually leverage techniques like statistical models or machine learning models to model on these features and then deploy this model if necessary for future usage based on the problem to be solved at hand. A typical standard machine learning pipeline based on the CRISP-DM industry standard process model is depicted below.
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Time Series Analysis in Python: An Introduction

Time series are one of the most common data types encountered in daily life. Financial prices, weather, home energy usage, and even weight are all examples of data that can be collected at regular intervals. Almost every data scientist will encounter time series in their daily work and learning how to model them is an important skill in the data science toolbox. One powerful yet simple method for analyzing and predicting periodic data is the additive model. The idea is straightforward: represent a time-series as a combination of patterns at different scales such as daily, weekly, seasonally, and yearly, along with an overall trend. Your energy use might rise in the summer and decrease in the winter, but have an overall decreasing trend as you increase the energy efficiency of your home. An additive model can show us both patterns/trends and make predictions based on these observations.
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30 Amazing Python Projects for the Past Year (v.2018)

For the past year, we've compared nearly 15,000 open source Python projects to pick Top 30 (0.2% chance).



This is an extremely competitive list and it carefully picks the best open source Python libraries, tools and programs published between January and December 2017. Mybridge AI evaluates the quality by considering popularity, engagement and recency. To give you an idea about the quality, the average number of Github stars is 3,707.
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A Beginner’s Guide to Data Engineering — Part I

The more experienced I become as a data scientist, the more convinced I am that data engineering is one of the most critical and foundational skills in any data scientist's toolkit. I find this to be true for both evaluating project or job opportunities and scaling one's work on the job.



In an earlier post, I pointed out that a data scientist's capability to convert data into value is largely correlated with the stage of her company's data infrastructure as well as how mature its data warehouse is. This means that a data scientist should know enough about data engineering to carefully evaluate how her skills are aligned with the stage and need of the company. Furthermore, many of the great data scientists I know are not only strong in data science but are also strategic in leveraging data engineering as an adjacent discipline to take on larger and more ambitious projects that are otherwise not reachable.



Despite its importance, education in data engineering has been li…

Machine Learning Zero-to-Hero: Everything you need in order to compete on Kaggle for the first time, step-by-step!

I recently came across Rachel Tomas's article on the importance and value of writing about what you learn, and Julia Evans's advice on why and how to write, and thus I have decided to follow their advice and write an article (for the first time ever!).



This article will be about everything I wish I had known a year ago , when I first decided I want to learn more about Data Science — it is meant for anyone who is interested in getting into Data Science, either as a hobby or as a potential career. Having done a MOOC first and knowing some basic Python will help you get the most out of this article, but it is not required by any means. This article is not meant to showcase anything impressive (sorry mom, dad, and potential employers), but rather to go over the basics and help beginners start off strong.
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The Art of Effective Visualization of Multi-dimensional Data

Descriptive Analytics is one of the core components of any analysis life-cycle pertaining to a data science project or even specific research. Data aggregation, summarization and visualization are some of the main pillars supporting this area of data analysis. Since the days of traditional Business Intelligence to even in this age of Artificial Intelligence, Data Visualization has been a powerful tool and has been widely adopted by organizations owing to its effectiveness in abstracting out the right information, understanding and interpreting results clearly and easily. However, dealing with multi-dimensional datasets with typically more than two attributes start causing problems, since our medium of data analysis and communication is typically restricted to two dimensions. In this article, we will explore some effective strategies of visualizing data in multiple dimensions (ranging from 1-D up to 6-D).
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