As mentioned above, Keras is a high-level API that uses deep learning libraries like Theano or Tensorflow as the backend.
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We will install Theano and Tensorflow as backend libraries for Keras, along with some more libraries which are useful for working with data h5py and visualization pydot, graphviz and matplotlib. By default, Keras is configured to use Tensorflow as the backend since it is the most popular choice.
Keras provides a very simple workflow for training and evaluating the models. It is described with the following diagram. Basically, we are creating the model and training it using the training data. Once the model is trained, we take the model to perform inference on test data. Let us understand the function of each of the blocks. Layers can be thought of as the building blocks of a Neural Network.
They process the input data and produce different outputs, depending on the type of layer, which are then used by the layers which are connected to them. We will cover the details of every layer in future posts. Keras provides a number of core layers which include. For creating a Sequential model, we can either pass the list of layers as an argument to the constructor or add the layers sequentially using the model.
For example, both the code snippets for creating a model with a single dense layer with 10 outputs are equivalent. An important thing to note in the model definition is that we need to specify the input shape for the first layer. The shapes of other layers are inferred by the compiler. In a supervised learning problem, we have to find the error between the actual values and the predicted value.
There can be different metrics which can be used to evaluate this error. This metric is often called loss function or cost function or objective function. There can be more than one loss function depending on what you are doing with the error.
In general, we use. Once the model is configured, we can start the training process. This can be done using the model. The usage is described below. We just need to specify the training data, batch size and number of epochs. Keras automatically figures out how to pass the data iteratively to the optimizer for the number of epochs specified.
The rest of the information was already given to the optimizer in the previous step. Once the model is trained, we need to check the accuracy on unseen test data. This can be done in two ways in Keras.
We will learn how to create a simple network with a single layer to perform linear regression. We will use the Boston Housing dataset available in Keras as an example. Samples contain 13 attributes of houses at different locations around the Boston suburbs in the late s. With the 13 features, we have to train the model which would predict the price of the house in the test data.
We use the Sequential model to create the network graph. Then we add a Dense layer with the number of inputs equal to the number of features in the data and a single output. Then we follow the workflow as explained in the previous section. We compile the model and train it using the fit command. Finally, we use the model. The output of model. It shows 14 parameters — 13 parameters for the weights and 1 for the bias.
After the model has been trained, we want to do inference on the test data. We can find the loss on the test data using the model. We get the predictions on test data using the model. Here we compare the ground truth values with the predictions from our model for the first 5 test samples. It can be seen that the predictions follow the ground truth values, but there are some errors in the predictions. Then you're missing out. Get faster resolution and technical support for open, high priority incidents — at a time that is convenient for you.
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Malware has been known to use this method to load itself when a user logs on to their computer. Loading in such a way allows the malware program to load in such a way that it is not easy to stop.
UserInit Key - This key specifies what program should be launched right after a user logs into Windows. The default program for this key is C: It is possible to add further programs that will launch from this key by separating the programs with a comma. This will make both programs launch when you log in and is a common place for trojans, hijackers, and spyware to launch from.
Shell Value - This value contains a list of comma separated values that Userinit. The default shell for Windows is explorer. Entries in these keys are started once and then are deleted from the key. If there is an- exclamation point preceding the value of the key, the entry will not be deleted until after the program completes, otherwise it will be deleted before the program runs.
This is important, because if the exclamation point is not used, and the program referenced in this key fails to complete, it will not run again as it will have already been deleted. All entries in this key are started synchronously in an undefined order. Run - These are the most common startup locations for programs to install auto start from. By default these keys are not executed in Safe mode.
It is generally found at:. User Profile Startup Folder - This folder will be executed for the particular user who logs in. This folder is usually found in:. If there is an exclamation point preceding the value of the key, the entry will not be deleted until after the program completes, otherwise it will be deleted before the program runs.
Explorer Run - These keys are generally used to load programs as part of a policy set in place on the computer or user. Load Key - This key is not commonly used anymore, but can be used to auto start programs. As most Windows executables use the user This makes it very difficult to remove the DLL as it will be loaded within multiple processes, some of which can not be stopped without causing system instability.
The files under this key are loaded automatically by Explorer.