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### Maximum Layers in "any" Neural Network [duplicate]

I have about 6 months of experience in building and using Neural Networks with no prior/formal training. As I explore this field further, I see a lot of discussions about determining how many layers/...
13k views

### Why do convolutional neural networks work?

I have often heard people saying that why convolutional neural networks are still poorly understood. Is it known why convolutional neural networks always end up learning increasingly sophisticated ...
4k views

### Neural Network Performs Bad On MNIST

I've been struggling with Neural Networks for a while now. I get the math behind backpropagation. Still as reference I'm using the formulas from here. The Network learns XOR: Prediction After ...
16k views

### Why should softmax be used in CNN

In the last layer of CNNs and MLPs it is common to use softmax layer or units with sigmoid activation functions for multi-class ...
3k views

### Depth of a Neural network

I was self-teaching myself. I totally understand why depth of a neural network affects the learning and how it differs than its width. But I am looking for some theoretical justification about it. ...
1k views

### More layers in NN give worse result

So I was working on a classification task with the help of a NN. The data-set was normalised, weights random between 0-1, and all the activations were sigmoid ...
168 views

### Is there any consensus on choosing an appropriate ML approach?

I am studying data science at the moment and we are taught a dizzying variety of basic regression/classification techniques (linear, logistic, trees, splines, ANN, SVM, MARS, and so on....), along ...
2k views

### Choosing layer hyper-parameters of a CNN

Context: I'm building a CNN on MATLAB to classify wallpaper groups. I'm using the following network type. CONV -> ReLU -> POOL -> CONV -> ReLU -> POOL -> FC -> ...
366 views

### Fully connected layer in deep learning

How to determine the best number of the fully connected layers in CNN? Can I use only one fully connected layer in CNN? How to determine the dimension of the fully ...
363 views

### How each layer of a neural net is responsible for one feature

Through my study of neural networks, I came across the idea that each layer of a neural network is responsible for recognizing one feature of the input data. For example, if we build a neural network ...
433 views

### Properly using activation functions of neural network

I'm trying to understand the hidden layers of neural networks. Input layer section covers the steps that I use before passing information to hidden layer where concerns appear. Input Layer: From my ...
539 views

### Neural Network beginner level tutorial

I am trying to build a simple multi layer perceptron Neural Network in Java, but apparently my calculations are off. I am looking for a beginner-level tutorial which can help me to understand how to ...
850 views

### How to obtain with a recurrent neural network the Xor function using keras? [closed]

I'm trying to implement a model of recurrent neural network to solve the XOR problem, but I am not still able to do that. Any hints?
733 views

### Predict method of the perceptron algorithm

Can someone explain to me how the predict method of the perceptron algorithm works? ...
416 views

### Should the different layers of deep learning models have same size or they should be changed based on a rule

I see a lot of people varying the width of each layer in a deep neural network. ie. Input->50->100->150->Output. I'm curious what, if any, are the advantages of this structure over static layer widths ...
164 views

### Neural Network Hidden Layer Selection

I am trying to build an MLP classifier model on a dataset containing 30000 samples and 23 features. What are the standards I need to consider while selecting the ...
237 views

### How does "linear algebraic" weight training function work?

This answer shows that linear and polynomial function weights can be trained using this matrix operation: $w = (X^TX)^{-1}X^Ty$ Therefore, algorithms such as gradient descent are not necessary for ...
191 views

### How to implement keras LSTM time series [closed]

I am learning how to implement Keras LSTM on a simple time series data. The dataset I'm using has $12$ columns and $300k$ rows. Each group of $200$ rows represents ...
130 views

### Is it a red flag that increasing the number of parameters makes the model less able to overfit small amounts of data?

I'm training a deep network (CNN-LSTM-CRF) for Named Entity Recognition. Is there a reason that increasing the number of parameters would make the network less able to overfit a small training set (~...
161 views

### Minimum Neurons in Neural Network

I use a brute-force mechanism to determine optimal hidden layers/neurons by incrementing the layers/neurons by 1 up to some maximums and then picking the optimal counts from the best performing model. ...
80 views

### Learning a logical function with a 2 layer BDN network - manual weight setting rule question?

So I am trying to construct a 2-layer network of binary decision neurons as proposed by McCullough and Pitts (1943) to learn a logical function (a composition of AND's and OR's) such as: \$((\neg x_1\...
80 views

### Handle Unbalanced data [closed]

I have a data-set with 2 target classes. In training dataset, the ratio of the 2 classes are 1:93 With my neural network, the current accuracy is 63%. I tried undersampling, oversampling, equal ...