top
Get exciting deals on all courses Use Coupon MM10 Click to Copy

Angular 2.1.0 Now Available

The minor release of Angular version 2.1.0 –incremental –metamorphosis is finally out. In this release, they have come up with an adoption of Semantic Versioning, which means there are not many changes added in this release so that they can replace it with 2.0.x.New features of Angular 2.1.0The capabilities of Angular connect : With the previous version, users were able to access lazy loaded content only after round trip to the server. In this version, routers have great support for preloading of the lazy loaded modules where users can experience the best parts of both the worlds.Animation in Angular have received some improvements by adding :enter and :leave Aliases for common void => * and* => void state changes.Also Read : Google releases Angular version 2.0.0In the previous version 2.0.0 Angular release, they have set some standards for the development processes:They have come up with the semantic versioning: Which means the version updations are relevant to the numbers. These releases do not affect the functionality, only minor changes will be added. Usually breaking changes will be announced in the major releases. For future planning purpose they have come up with time-based cycles: The cycles have been planned as per the below schedule so that developers can easily adapt to the changes.They have come with Deprecation policy so that developers will be informed in prior about the API changes: Breaking changes are troublesome, but these changes are required as part of innovation. Dependencies or transitions are done in the platform itself. To get easily adapted to the changes, they are implementing deprecation policy and trying to minimize the number of breaking changes in Angular.They have given the proper differentiation between the stable and experimental APIs: If you have gone through the Angular API docs, you have might have noticed some marked APIs as experimental. Experimental APIs are good enough to be in production, only field testing is required to validate and work well for different  use cases. Semantic versioning is followed by experimental APIs but they don't follow deprecation policy. When you start working with Experimental APIs changes are expected but they do not have deprecation path.The Scope of their Public API surface is well defined: Angular is a group of packages, tools, and sub-projects. To avoid the usage of private APIs unexpectedly, terms and conditions are documented in public API surface.
Rated 4.0/5 based on 20 customer reviews
  1. Home
  2. Magazine
  3. Angular 2.1.0 Now Available
Normal Mode Dark Mode

Angular 2.1.0 Now Available

Geneva Clark
What's New
17th Oct, 2016
Angular 2.1.0 Now Available
The minor release of Angular version 2.1.0 –incremental –metamorphosis is finally out. In this release, they have come up with an adoption of Semantic Versioning, which means there are not many changes added in this release so that they can replace it with 2.0.x.

New features of Angular 2.1.0

  • The capabilities of Angular connect : With the previous version, users were able to access lazy loaded content only after round trip to the server. In this version, routers have great support for preloading of the lazy loaded modules where users can experience the best parts of both the worlds.
  • Animation in Angular have received some improvements by adding :enter and :leave Aliases for common void => * and* => void state changes.

Also Read : Google releases Angular version 2.0.0

In the previous version 2.0.0 Angular release, they have set some standards for the development processes:

  • They have come up with the semantic versioning: Which means the version updations are relevant to the numbers. These releases do not affect the functionality, only minor changes will be added. Usually breaking changes will be announced in the major releases.
  •  For future planning purpose they have come up with time-based cycles: The cycles have been planned as per the below schedule so that developers can easily adapt to the changes.

angular 201 major release cycle

  • They have come with Deprecation policy so that developers will be informed in prior about the API changes: Breaking changes are troublesome, but these changes are required as part of innovation. Dependencies or transitions are done in the platform itself. To get easily adapted to the changes, they are implementing deprecation policy and trying to minimize the number of breaking changes in Angular.

  • They have given the proper differentiation between the stable and experimental APIs: If you have gone through the Angular API docs, you have might have noticed some marked APIs as experimental. Experimental APIs are good enough to be in production, only field testing is required to validate and work well for different  use cases. Semantic versioning is followed by experimental APIs but they don't follow deprecation policy. When you start working with Experimental APIs changes are expected but they do not have deprecation path.

The Scope of their Public API surface is well defined: Angular is a group of packages, tools, and sub-projects. To avoid the usage of private APIs unexpectedly, terms and conditions are documented in public API surface.
Geneva

Geneva Clark

Blog Author
Geneva specializes in back-end web development and has always been fascinated by the dynamic part of the web. Talk to her about modern web applications and she and loves to nerd out on all things Ruby on Rails.

Leave a Reply

Your email address will not be published. Required fields are marked *

SUBSCRIBE OUR BLOG

TRENDING BLOG POSTS

MIT’s new automated ML runs 100x faster than human Data Scientists

According to Michigan State University and MIT, automated machine learning system analyses the data and deliver a solution 100x faster than one human. The automated machine learning platform which is known as ATM (Auto Tune Models) uses cloud-based, on demand computing to accelerate data analysis. Researchers of MIT tested the system through open-ml.org, a collaborative crowdsourcing platform, on which data scientists collaborate to resolve problems. They found that ATM evaluated 47 datasets from the platform and the system was capable to deliver a solution that is better than humans. It took nearly 100 days for data scientists to deliver a solution, while it took less than a day for ATM to design a better-performing model. "There are so many options," said Ross, Franco Modigliani professor of financial economics at MIT, told MIT news. "If a data scientist chose support vector machines as a modeling technique, the question of whether she should have chosen a neural network to get better accuracy instead is always lingering in her mind." ATM searches via different techniques and tests thousands of models as well, analyses each, and offers more resources that solves the problem effectively. Then, the system exhibits its results to help researchers compare different methods. So, the system is not automating the human data scientists out of the process, Ross explained. "We hope that our system will free up experts to spend more time on data understanding, problem formulation and feature engineering," Kalyan Veeramachaneni, principal research scientist at MIT's Laboratory for Information and Decision Systems and co-author of the paper, told MIT News. Auto Tune Model is now made available for companies as an open source platform. It can operate on single machine, on-demand clusters, or local computing clusters in the cloud and can work with multiple users and multiple datasets simultaneously, MIT noted. "A small- to medium-sized data science team can set up and start producing models with just a few steps," Veeramachaneni told MIT News. Source: MIT Official Website  
Rated 4.0/5 based on 20 customer reviews
MIT’s new automated ML runs 100x faster than human Data Scientists

MIT’s new automated ML runs 100x faster than human Data Scientists

What's New

Gartner says, by 2020, 2.3 Million jobs will be created by Artificial Intelligence

On Monday, October 2, Peter Sondergaard at Gartner Symposium said that "AI will be a net job creator starting in 2020". How robots and AI will change the future of jobs is the big question now in everyone’s mind. According to Gartner, 8 million candidates are working in the IT field but, out of them only 1,250 to 1500 candidates are familiar with artificial intelligence. Simultaneously, 10% of companies are looking to hire candidates who are expert in machine learning and AI, to yield better results. Sondergaard said that by the year 2020, AI will destroy nearly 1.8 million jobs, but at the same time, it will create 2.3 million jobs. This means that AI will bring about 5,00,000 job openings globally. He also stated that "One year later, AI augmentation of the workforce will create about $3 trillion in business value, while saving billions of hours of work … so AI will help find, develop and augment your people. AI will be a net job creator starting in 2020." Gartner analyst stated that organizations should be more innovative towards bringing the hidden skills and power of existing employees to light. “Gartner predicts one in three jobs will be converted to software, robots and smart machines by 2025,” said Gartner research director Peter Sondergaard. “New digital businesses require less labor; machines will make sense of data faster than humans can.” Source: Gartner Official Blog  
Rated 4.0/5 based on 20 customer reviews
Gartner says, by 2020, 2.3 Million jobs will be created by Artificial Intelligence

Gartner says, by 2020, 2.3 Million jobs will be created by Artificial Intelligence

What's New

Iot market value will exceed 1.4 trillion USD by 2021

A recent press release from International Data Corporation (IDC), has forecast the spending on IoT market to grow cumulatively up to 16.7 percent by 2017, worldwide, and is expected to reach over 800 billion USD.By 2021, this spending is expected to reach nearly 1.4 trillion USD, led by the company's investment services, connectivity, hardware and software that enable the IoT worldwide. "The discussion about IoT has shifted away from the number of devices connected and the true value of IoT is being realised when the software and services come together to enable the capture, interpretation, and action on data produced by IoT endpoints. With our Worldwide IoT Spending Guide, IDC provides insight into key use cases where investment is being made to achieve the business value and transformation promised by the Internet of Things"- said Carrie MacGillivray, vice president, Internet of Things and Mobility at IDC. The use cases of IoT that are expected to attract the largest investment includes freight monitoring, production asset management and manufacturing, that will attract the largest investments. The smart grid technologies for gas, water, electricity and smart buildings expect to see significant investment gains in the next few years. Long tail investments in smart home technologies and in-store contextual marketing will grow exponentially over the next five years in IoT market. The IoT hardware spending will be focussed on sensors and modules that connect end-points to networks, whereas software and services spending will dominate in the spheres of content, installation and IT services. As organisations are adopting new innovative services by different marketers, a lot of threats are found.To safeguard the system from these threats, it is very important to upgrade the existing security systems to establish optimal business outcome and justify ROI. In terms of industry investments, transportation and manufacturing have been making 85 billion USD and 183 billion USD respectively. More utilities are coming together for IoT technologies, with an expected spending of around 66 billion USD.
Rated 4.0/5 based on 20 customer reviews
Iot market value will exceed 1.4 trillion USD by 2021

Iot market value will exceed 1.4 trillion USD by 2021

What's New

Follow Us On

Share on

other Blogs