< Previous “我不知道”-...>接下来> 2018年最佳 - 深度学习版 Posted byJohanna Pingel那2018年12月20日 10 views (last 30 days) |0.Likes|2评论 今天,让我们回到“2018年最佳”之旅。我将突出2018年的特定帖子和功能,这是值得第二个外观。 深入学习...... 我们很高兴报告我们在新功能,例子和视频中一直在这里花了很多时间,以获得不同的深度学习应用领域。我们仍然倾向于重点焦点图像,以来: 这项研究仍然倾向于这种方向和 这真的很有趣 但现在,我们也在转移对其他领域的重点,首先是:信号和时间序列数据。沿着这些线路,有各种例子来检查: This is theone link you should bookmark today://www.tatmou.com/help/deeplearning/examples.html.这会通过每个版本进行更新,并为所有应用程序区域提供了一个很大的示例列表。 Doc中的深度学习示例 An interesting article in the 2018 “ A sample page of "News and Notes" featuring deep learning以下部分中的“深入学习...”有更多的资源。 Videos It was a great year for the creation of webinars and videos: 加布里埃尔和我做了30分钟的视频图像处理和计算机视觉那which of course has deep learning in it! This is a great intro for anyone just getting started. I created a “What is Computer Vision“视频,刚刚去过的视频,(特别感谢我们的视频团队!)This is for the beginner crowd interested in computer vision, so this may not be as relevant to this group! Along the same line, there's a new什么是机器学习视频,由...创建Loren Shure.。This is a quick and thorough look at Machine Learning that's great for the beginner crowd, or anyone that hears terms like 'Machine Learning' and 'Deep Learning' and wants to learn more. 新的网络研讨会可用于深入学习信号数据,称为:“深度学习信号和声音“ A new webinar is available forText Analytics。 Here's a recap of these videos with links in the images: 图像处理和计算机视觉 Computer Vision Video Signals and Sound Webinar 文本分析网络研讨会 “New Stuff" We have also been hard at work creating new content. I’m just going to bucket this as “new stuff.” 备忘单:这是一个页面引用(随便称为“深度学习作弊表“): 很高兴拥有印刷和发布到您的办公室墙壁的相关深度学习功能。 Deep Learning is not the only cheat sheet available. A successful机器学习作弊表is also available for you to use. Here are 5 cheat sheets you may find useful: (The images are links to the PDFs) Deep Learning Machine Learning 时间序列预处理↓↓ 直播编辑 导入/导出数据 ↑ I strongly recommend this one! Solutions page updates:我们不断更新网络上的内容:我们对我们的新看IPCV solutions page和我们的深度学习金宝搏官方网站解决方案页面。这两个页面都有链接到新内容。 One final thing提到是一个新的例子方法,使它们更加互动。我们发布了A.Deep Learning Browser Example那which allows you to try out a simple example to experience what deep learning with MATLAB would look like. This is great for beginners and people who don't have access to MATLAB yet (no license required to try this example). Tell your friends! 新特性! 每年,我们有2个版本的product. This year brought us R2018a and R2018b.(我们在名字上非常可预测)。 对于R2018A,其中一个突出功能是深度学习网络分析仪,史蒂夫博彩在这里:https://blogs.mathworks.com/deep-learning/2018/04/30/deep-learning-network-analyzer/那 Although Network Analyzer was released in R2018a, it’s worth noting that this feature is now part of the深度网络设计器应用程序。You can now import networks into the app, and use the network analyzer to check the connections. Steve wrote a relevant post for more R2018a highlightshere。 InR2018b那we decided to try something different and used a video approach instead. Gabriel did an excellent job highlighting the important features of 18b, along with some of the key features from recent releases. You can find the video on the solutions page, orthis linkdirectly to the video.Please be aware this video plays automatically, which made me jump out of my seat with my speaker up too loudly! Final Thoughts 当我们走进新的一年时,我喜欢在过去一年中的事情以及我们可以做得更好的事情。我的新年的目标是增加帖子的频率,并开始发布较短的内容,因为它可用。我正在寻找建议on what you’d like to see more and/or less of. Also, do you agree with my top 4 list? Anything else I should have mentioned? Leave a comment below! 节日快乐,在2019年见!! MathWorks准备好了假期! | 你现在关注这个博客帖子 You will see updates in your活动饲料。 您可以收到电子邮件,具体取决于您的电子邮件通知偏好。 类别: Deep Learning < Previous “我不知道”-...>接下来> 也可以看看 深入学习的深度潜水视频 Blogs 回顾2019年 Blogs 出口到ONNX. Blogs 鹤壁学习 学习AI的深层架构 Deep Learning ,Deep neural network- CNN Emotion Recognition Comments 要发表评论,请点击here要登录您的MathWorks帐户或创建新的。