Archives for Cheat Sheets

23 Nov

CheatSheet | Long Short-Term Memory (LSTM)

Recurrent neural networks possess a problem of vanishing gradients and eventually running out of memory to save essential information. To overcome this a modified version of RNN called LSTM or long short term memory was introduced. It is similar in operation to RNN but the difference lies in the cell states. To download the cheat…

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16 Nov

CheatSheet | Random Forest in R

A random forest model acts as an ensemble consisting of multiple decision trees. Each decision tree in the random forest takes inputs and gives the class prediction as output. The class with the highest number of votes becomes the model decision. The random forest can be used for both classification and regression. To download the…

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12 Nov

CheatSheet: Python Collections

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image-17531

Python Collections are containers that are used to store collections of data thatare list, dictionary, tuple, etc. These are built-in collections. Several modules havebeen developed that provide additional data structures to store collections ofdata. Python collections module helps to improve the functionalities of thebuilt-in collection containers. Let us see what are some of the most…

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22 Oct

CheatSheet: Convolutional Neural Network (CNN)

It is also termed as ConvNet that is a Deep learning algorithm that inputs an image, draws different feature maps using different kernels that allocates learnable weights to different objects in the image so as to differentiate from one another. The algorithm is widely used for various Image related tasks like classification, segmentation etc. Let…

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18 Oct

CheatSheet: Decision Tree in R

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image-16786

A decision tree is a machine learning algorithm that represents the inputs and outcomes in the form of a tree. They are used for building both classification and regression models. The decision tree contains nodes and edges which represent the events and decisions respectively. The first node is called the root node and branches into…

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14 Oct

CheatSheet: Random Forest in Python

image-16677
image-16677

Random Forest is an ensemble tree-based algorithm. It consists of a set of decision trees that are randomly selected from a subset of the training data. The final class of the testing data point is selected on the basis of aggregate votes from other decision trees. To download the cheatsheet, please login below and follow…

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