This Week’s Links
Fragmented Podcast – Ep #134: Get Effective Help with an SSCCE
In this episode of Fragmented, Donn (@donnfelker) talks about how you can get effective help with your coding problems with an SSCCE – a Simple, Self-Contained, Correct (Compilable), Example. Using an SSCCE provides others with a quick, concise way to examine the problem without extraneous libraries, UI toolkits and various other parts of your application that do not matter to the problem at hand. Donn breaks down each component of the SSCCE so you can wrap your head around what you need to get help quickly.
Looking forward with Google Play
After releasing Android 9 Pie this week, Google continues to push the Android platform forward, and is looking to provide new ways to distribute developers’ apps efficiently, help developers discover and engage their work, and improve the overall security of our ecosystem. Read more about Google’s big milestones around helping developers reach more users in this post.
Building a Custom Machine Learning Model on Android with Tensorflow Lite
While building a custom TensorFlow Lite model can sound really scary, developers don’t need to be a Machine Learning or TensorFlow expert to add Machine Learning capabilities to your Android app. Learn more about adding Machine Learning to your next project in this article.
Google Developers Launchpad Introduces The Lever, Sharing Applied-Machine Learning Best Practices
Google Developers Launchpad announced a new resource called The Lever, which is for sharing applied-Machine Learning (ML) content to help startups innovate and thrive. This new partnership includes experts and leaders from across Google and Alphabet, The Lever will publish the Launchpad community’s experiences of integrating ML into products, and will include case studies, insights from mentors, and best practices from both Google and global thought leaders.
This post focuses on two variants of stepwise selection: (1) The linear stepwise selection method of Efroymson and (2) a custom logistic regression stepwise selection method using two passes through the data. Both methods rely on using a simple approach to selecting the most relevant features. Learn more in this post.
(these are pulled from Androiddevdigest.com/jobs)
Google Explains how AI powers Android Pie’s Smart Linkify
Android Pie, the newest version of Google’s mobile operating system, launched earlier this week, and one of its niftiest features is Smart Linkify. It’s an API that adds clickable links when addresses, phone numbers, and other such entities are detected in text. Learn more about the magic behind this feature in this article.
The Machine Learning Behind Android Smart Linkify
Smart Linkify is a new version of the existing Android Linkify API. It is powered by a small feed-forward neural network with low latency and small inference code, and uses essentially the same machine learning technology that powers Smart Text Selection to now also create links.
Android Operating System: One Potential Vulnerability per 4000 Lines of C++ Code
For many years, Andrey Karpov has been publishing articles on code quality, and bugs reviews of open source projects.Recently, the open source Android operating system has become of interest for him. He researched that part of the operating system code and discovered by using the PVS-Studio tool, it becomes possible to detect at least one security defect (potential vulnerability) per 4000 lines of code.
Android Pie SDK is now more Kotlin-friendly
As part the Android 9 announcement, Google has also released a new Android SDK containing nullability annotations for some of the most frequently used APIs. This will preserve the null-safety guarantee when a developer’s Kotlin code is calling into any annotated APIs in the SDK.
Caster.io: Setting up the Remote Layer for Testing
Within Clean Architecture, the Remote layer allows us to abstract the remote source of data that our application uses. To ensure that this layer operates as intended through time, we’re going to need tests. In this lesson we’ll be setting up the factory classes so that we can create mock data within the tests that we write.
Caster.io: Creating the Data Models for the Remote Layer
Within Clean Architecture, the Remote layer allows us to abstract the remote source of data that our application uses. In this lesson, we’re going to begin building our remote layer by creating the data models for the data that we retrieve back from the external remote source.
A light, powerful and easy to use Calendar Widget with a number out of the box features that include infinite vertical scrolling in both directions and setting date boundaries to restrict scrolling inside of a specific time period. Read more about this Calendar Widget and how to use it in this post.
Slices are template views which have the ability to show and interact with content from an app from Google Search and later, places like the Google Assistant. Take a look at this sample Android application, which demonstrates the usage of different types of Android Slices.