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In this guide we will learn about Reinforcement Learning Module in Pybrain. Reinforcement Learning (RL) is an important part in Machine Learning. Reinforcement learning makes the agent learn its behaviour…

In this guide, we will learn connections in Pybrain. A connection works similar to a layer; an only difference is that it shifts the data from one node to the…

In this guide, we will discuss about Layers in Pybrain. Layers are basically a set of functions that are used on hidden layers of a network. We will go through…

In this guide, we will learn Training Network Using Optimization Algorithms. We have seen how to train a network using trainers in pybrain. In this chapter, will use optimization algorithms…

In this guide, we will discuss working with recurrent networks in Pybrain. Recurrent Networks is the same as feed-forward networks with the only difference that you need to remember the…

In this guide, we will discuss about working with feed-forward networks in pybrain. A feed-forward network is a neural network, where the information between nodes moves in the forward direction…

In this chapter, we will discuss about testing network in Pybrain and we are going to see some example where we are going to train the data and test the…

In this guide, we will discuss about training datasets on networks. So far, we have seen how to create a network and a dataset. To work with datasets and networks…

In this chapter, we will learn about importing data for datasets and how to get data to work with Pybrain datasets. The most commonly used are datasets are − Using…

In this guide, we will discuss about pybrain datasets types. Datasets are data to be given to test, validate and train on networks. The type of dataset to be used…