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A quick intro into IoT networking. Networks around the world are going through a massive transformation in which edge computing devices and edge infrastructure development hold a key role. This edge revolution is to leverage the potential of IoT that will be unleashed on the back of 5G roll out in future not so far.

Article then briefly explains:

• Multi-Access Edge Computing
• Fog computing
• Cloudlets
• Micro Data Centers

Fog computing, fog networking or merely “fogging”, is a term used to described a decentralized computing infrastructure which both extends cloud computing to the edge of a network. It is also an attempt to reduce the data transported to the cloud for processing, analysis and/or storage.

Learn more in this short article.

An older article by jjwalkarn about Convolutional Neural Networks. Convolutional Neural Networks (ConvNets or CNNs) are a category of Neural Networks that have proven very effective in areas such as image recognition and classification.

ConvNets have been successful in identifying faces, objects and traffic signs apart from powering vision in robots and self driving cars.

The LeNet Architecture is few decades old. LeNet was one of the very first convolutional neural networks which helped propel the field of Deep Learning. This pioneering work by Yann LeCun was named LeNet5 after many previous successful iterations since the year 1988.

The article then explain in detail main operations in the ConvNet:

• Convolution
• Non Linearity (ReLU)
• Pooling or Sub Sampling
• Classification (Fully Connected Layer)

In the article you get the main concepts behind Convolutional Neural Networks in simple terms. Plus, added is a treasure of links to further reading. Excellent read!

Ross Bulat wrote a tutorial about building a scalable Node.js library based on Promises. In it he explains how to tackle large async / await Promise based libraries.

With the goal of supporting medium to large scale applications, libraries need to be coherent and manageable, yet be flexible and usable in your promise based execution.

The author covers on an example of MongoDB based API:

• Explaining requirements in terms of
  • scalability, economics, Promise based (with links to more resources)
• Importing MongoDB Promises as database client
• Structuring your exports
• Promise example: auth token valid?
• Extending the API call with more Promises

Useful for any developer struggling with Promises. Good read!

Tutorial by Michael Herrmann explains how you can use PyQt5 to build a desktop app with Python. It covers everything from the best way to set up PyQt in 2018, to compiling your app and distributing it to other people’s computers.

In essence it explains:

• What is PyQt5?
• How to install PyQt
• How to create a GUI
• What are widgets
• How to build layouts
• How to implement custom styles

… and much more. Sweet and to the point tutorial which gives you basic understanding of PyQt and introduce you into desktop apps development with Python 3.

As a bonus you will also learn how to create a standalone version of your app. That is, a binary executable that other people can run on their systems without having to install anything. Great!

Interesting reading from Mike Bell about efficient applications monitoring in Agile environment with daily deploys of hundreds of code changes to the web application for customer-facing websites. Each change has the potential to impact performance for better or worse. They carefully monitor KPIs such as page load times to catch regressions, identify opportunities for speedups, and to verify that improvements work in the real world.

RUM systems use JavaScript and standard browser APIs like PerformanceTiming to record load times experienced by real customers.

Client-side monitoring of page load times in the browser is known as Real User Monitoring, or RUM. RUM systems use JavaScript and standard browser APIs like PerformanceTiming to record load times experienced by real customers. In the article you will get information on:

• What is RUM?
• How was RUM implemented in Wayfair’s engineering team
• Introduction into InfluxDB
• InfluxDB schema for RUM and how to optimize schema
• Dashboards
• How team got visibility into the experience of real customers

Measuring performance on high-traffic e-commerce web sites is challenging. Excellent read!

An older article encapsulating thoughts by Jen Simmons on topic of six layout myth. Every website reaches for an identical 12-column symmetrical grid. Every site uses the same shapes and patterns over and over. And we are totally bored.

We should start asking ourselves what kind of page layout will best serve this project? How can we tap into a hundred years of graphic design practice to communicate through our layout? Our biggest challenge will be fighting the limitations of our imagination. We developed powerful habits over the last 10 years.

Author then considers these design myths for web development:

• Myth 1: Everything must be a floating bar of soap
• Myth 2: Rectangles; only rectangles
• Myth 3: We can’t control the fold
• Myth 4: 12 columns is the best
• Myth 5: We have to use a layout framework
• Myth 6: We are stuck in a rut because of RWD

Interesting read with clear message – if you can let go of these myths, your work will stand out. Visual exmaples includes. Great!

Valentino Gagliardi published on his blog tutorial how to do REST with Django framework 2 and React. If you need quick API prototype quickly and is build for development speed.

Django is ideal web framework for rapid prototyping: it lets developer write less code, ship a MVP as soon as possible, provides a solid foundation for extending the project.

Tutorial focuses (among others) on:

• Setting up a Python virtual environment, and the project
• Bulding a Django application
• Creating a Django model
• Basic understanding what to test with TDD and coverage
• Django REST serializers
• Seeding the database

… and much more. This is lengthy tutorial with code examples provided and explained, links to further reading and Q&A from users following this tutorial. Good job!

An article by Vaibhav Verma, an User Experience Designer at Haptik, about his experience with designing the smart chatbots over 4 years period. He has designed more than 50 chatbots across various domains and use cases.

First, it’s important to understand what a chatbot actually is. I like to define it as an interface to get a task done via a text or voice based conversation with a robot, sometimes aided by a human.

Through Machine Learning algorithms, chatbots can learn appropriate answers to specific user queries over time, for which they no longer require training.

Personality is very important for a chatbot. Chat works the best if kept short and simple. Some steps to make a good chatbot:

• Consider use-cases where chat works best
• Define the exact goal of the bot
• Work on the personality and tonality
• List out the specific tasks a user can perform

… and much more in the article, including frequently used prototyping tools, how to make handoff kit to developer, builder platforms etc. Very insightful!

Jarno Walgemoed short introduction on some new interesting features in Kotlin 1.3. Kotlin’s built-in null-safety makes it easy for us to write code that’s less error-prone and less susceptible to the unwanted and unexpected NullpointerException at runtime.

Kotlin is introducing Contracts in the upcoming 1.3 release in which we can use contracts to tell the compiler how a function behaves and what results are implied, so we can benefit from improved smart-casts.

Starting with Kotlin 1.3, we can start defining contracts for our functions.

Supplying the compiler with contracts for applicable functions can help clean up code on the call site and remove redundant null-checks.

You will find example code describing a User and implementation defining the contracts using Returns and Implies. Excellent intro into contracts in Kotlin!

Olawale Aladeusi blog post about building Application Programming Interface in Python. This shall be a very easy to learn path in creating RESTFUL API using Python and Flask micro-framework.

In the tutorial he takes on the journey of allowing all four basic CRUD (Create, Read, Update and Delete) operations. Flask is a micro web framework written in Python. It is called a micro-framework because it does not require any specific libraries or tools.

Author also uses PostgreSQL relational database for this project. You will get information how to:

• Set up project virtual environment using pipenv
• Installing Project Dependencies
• How to create meaningful project structure
• Database basics
• Flask configuration
• Model app

Detailed steps with explanation of the code examples is provided. You should have enough information about configuring Flask environment, creating models, making and applying migrations to the database, grouping resources using Flask blueprint, validating the authenticity of a user using JWT token and also complete set up for all RESTful endpoints.

Excellent intro into Python’s Flask!