Loading presentation...

Present Remotely

Send the link below via email or IM


Present to your audience

Start remote presentation

  • Invited audience members will follow you as you navigate and present
  • People invited to a presentation do not need a Prezi account
  • This link expires 10 minutes after you close the presentation
  • A maximum of 30 users can follow your presentation
  • Learn more about this feature in our knowledge base article

Do you really want to delete this prezi?

Neither you, nor the coeditors you shared it with will be able to recover it again.


Make your likes visible on Facebook?

Connect your Facebook account to Prezi and let your likes appear on your timeline.
You can change this under Settings & Account at any time.

No, thanks

Copy of Copy of Neural Network

No description

Michael Steffen

on 12 May 2013

Comments (0)

Please log in to add your comment.

Report abuse

Transcript of Copy of Copy of Neural Network

What is a Neural Network A neural net is an artificial representation of the human brain that tries to simulate its learning process. An artificial neural network is often called a “Neural Network”.

Traditionally, the word neural network is referred to a network of biological neurons in the nervous system that process and transmit information. Basal principle Artificial Neural networks What it is? Based on
biological neural network 前不久,Google X實驗室正式發佈了一種新型的人工智能技術:該系統具有強大的自我學習功能。如果該技術投入使用,將使Google的軟件更加智能化,而首先受益的是語音識別軟件。
据悉,使用新型網絡后的Google語音軟件的正确率有了20%-25%的提升,改進之後甚至可以識別方言,Google的其他品也将在新AI技的帮助下得到改善。比如,Google的圖像搜索工具将不再依賴文本描述就能更好地理解内容;无人汽車及Google Glass都将从中受益。 第一個真正具有實用意義的神經網絡是BP神經網絡。BP(Back Propagation)网是1986年由Rumelhart和McCelland首的科学家小組提出,是一按誤差逆播算法訓練的多層前饋网,是目前使用最广泛的神經網絡模型之一。BP网能學習和存儲大量的輸入-輸出模式映射關系,而无需事前提示描述映射系的数学方程。它的學習規則是最速下降法,通過誤差逆傳播来不断調整網絡的權和閾,使網絡輸出的誤差平方和最小。 Thank You for Listenning! it is a kind of simulative
arithmetic Application Finance Prediction Weather Forcast Writing Identification Driveless Car Simultaneous Interpretation Thank you for your listening! The Future
Full transcript