Adobe非常慷慨,满足了我申请Flex Builder Pro 3的10个授权的心愿。

博主成功申请到Adobe FlexBuilder Pro3的10个教育版授权,并分享了申请过程及心得。起初因提交资料不充分被拒,后通过提供更详尽证明及使用.edu.cn邮箱成功获批。

哈哈,获得了Adobe Flex Builder Pro 3的10个授权(教育版的),真是棒极了。虽然一个也够本人用了,不过为了以后考虑,多要了几个。正在使用Flex开发学校的一个系统,比较爽啊,Flex 2的东西在Flex 3里照样有效,有关Flex 3的相关书籍快点推出那就更好啦。

第一次申请,提交了自己的教师资格证,用的是gmail的邮箱,结果被denied,伤心了一会。

下面是拒信。

Dear wang jianbin,

Thank you for your interest in Adobe Flex Builder. Unfortunately, you do not qualify for the  free version. There are several reasons why your application may have been denied:
1. You may not be a current student, a faculty member or an employee at an educational institution
2. The credentials you uploaded may not be adequate to establish your eligibility.

If you believe that your application has been denied in error, please contact info@flexregistration.com.

Regards,
Adobe

估计Adobe认为我提交的材料不够详细、充分,于是第二次把自己的工作证,讲师证也扫描了,用edu.cn的信箱申请,还好这次通过了。

下面是申请通过。

Adobe Flex application accepted

Dear Wang Jianbin,

Thanks for your interest in Adobe Flex Builder. Developers all around the world have built some amazing applications with Flex Builder; you can see their work at the Flex Showcase. We encourage you to build your own application and then submit it to the Flex Showcase so others can see what you've built.

Downloading Flex Builder
If you have not downloaded Flex Builder, please download the trial version to get started.


Activating Flex Builder
Once you've downloaded Flex Builder, you can enter the following serial numbers to activate your product and the charting components.

Serial Number: xxxx-xxxx-xxxx-xxxx-xxxx-xxxx
Seats : 10

 

Using Flex Builder
The fastest and easiest way for you to get started with Flex Builder is to visit the Getting Started section on the Flex Developer Center. Go through the tutorials there and see how easy it is to build your own Flex applications.

We look forward to seeing what you build.

The Adobe Flex Team
Flex on Facebook

根据原作 https://pan.quark.cn/s/459657bcfd45 的源码改编 Classic-ML-Methods-Algo 引言 建立这个项目,是为了梳理和总结传统机器学习(Machine Learning)方法(methods)或者算法(algo),和各位同仁相互学习交流. 现在的深度学习本质上来自于传统的神经网络模型,很大程度上是传统机器学习的延续,同时也在不少时候需要结合传统方法来实现. 任何机器学习方法基本的流程结构都是通用的;使用的评价方法也基本通用;使用的一些数学知识也是通用的. 本文在梳理传统机器学习方法算法的同时也会顺便补充这些流程,数学上的知识以供参考. 机器学习 机器学习是人工智能(Artificial Intelligence)的一个分支,也是实现人工智能最重要的手段.区别于传统的基于规则(rule-based)的算法,机器学习可以从数据中获取知识,从而实现规定的任务[Ian Goodfellow and Yoshua Bengio and Aaron Courville的Deep Learning].这些知识可以分为四种: 总结(summarization) 预测(prediction) 估计(estimation) 假想验证(hypothesis testing) 机器学习主要关心的是预测[Varian在Big Data : New Tricks for Econometrics],预测的可以是连续性的输出变量,分类,聚类或者物品之间的有趣关联. 机器学习分类 根据数据配置(setting,是否有标签,可以是连续的也可以是离散的)和任务目标,我们可以将机器学习方法分为四种: 无监督(unsupervised) 训练数据没有给定...
评论 1
添加红包

请填写红包祝福语或标题

红包个数最小为10个

红包金额最低5元

当前余额3.43前往充值 >
需支付:10.00
成就一亿技术人!
领取后你会自动成为博主和红包主的粉丝 规则
hope_wisdom
发出的红包
实付
使用余额支付
点击重新获取
扫码支付
钱包余额 0

抵扣说明:

1.余额是钱包充值的虚拟货币,按照1:1的比例进行支付金额的抵扣。
2.余额无法直接购买下载,可以购买VIP、付费专栏及课程。

余额充值