deep learning coursera github

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iOS Deep Learning (Block comprehensive analysis)

*tftext); @end//nextviewcontorller.m file-(ibaction) popbtnclicked: (ID) Sender { if (self). Nextviewcontrollerblock) { self.Nextviewcontrollerblock (selfinputtf. Text); } [self. Navigationcontroller popviewcontrolleranimated:YES];} And then look at the contents of the Viewcontroller file,-(IBAction)btnClicked:(id)sender{NextViewController*nextVC=[[NextViewControlleralloc]initWithNibName:@"NextViewController"bundle:nil];nextVC.NextViewControllerBlock=^(NSString*tfText){[selfresetLabel:tfT

Deep Residual Network _ depth Learning

Deep Residual network in the 2015 ILSVRC competition to achieve the first achievement, ICLR2016 is also one of the key issues. Its main idea is simply to add a hop to bypass some layers of connectivity on a standard feedforward convolution network. Each bypass layer produces a residual block (residual blocks), and the convolution layer predicts the residuals of the input tensor. As shown in the following illustration: Common depth feedforward networ

iOS Deep Learning (UITableView Series 4: Customizing Cells with Xib)

-(NSInteger)tableView:(UITableView*)tableViewnumberOfRowsInSection:(NSInteger)section{return[_personscount];}-(UITableViewCell*)tableView:(UITableView*)tableViewcellForRowAtIndexPath:(NSIndexPath*)indexPath{static NSString*simpleIdentify=@"SimpleIdentify";UITableViewCell*cell=[tableViewdequeueReusableCellWithIdentifier:simpleIdentify];NSArray*nib=[[NSBundlemainBundle]loadNibNamed:@"CustomTableViewCell"owner:selfoptions:nil];if([nibcount]>0){self.customCell=[nibobjectAtIndex:0];cell=self.customCe

--convlstm principle and TensorFlow realization of spatial deep learning

Reproduced in the Daily Digest of deep learning, convlstm principle and its tensorflow realizationThis document references convolutional LSTM network:a machine learning approach forPrecipitation nowcasting Today introduced a very famous network structure--convlstm, it not only has the LSTM time series modelling ability, but also can like CNN to portray the local

What are some interesting and easy-to-implement papers about deep learning?

He is good at python, theano, and keras frameworks. He wants to introduce some new and interesting papers. Note: painting has been realized. Reply content: I have already received more than 400 likes without knowing it. Recently, I have finally made some time to add more interesting things. The content in the back will not be broken down ...... (No more than deep learning ......) 0.

Deep Learning notes ------ configure and install caffe-cpu only mode in linux, and install caffecpuonly

Deep Learning notes ------ configure and install caffe-cpu only mode in linux, and install caffecpuonly This article is suitable for beginners to learn the simplest way to configure caffe. This is the most silly configuration method I have summarized after reading the methods of various great gods on the Internet. I am also suffering from attacks and growth in the Process of constantly configuring caffe @.

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