Archives for Cheat Sheets
In order to remove noise from an image, images are blurred or made less clear. This isusually done with low pass filter kernels and helps in smoothening the image. There are three main types of blurring with OpenCV python library. To download the CheatSheet, please login below and follow our Instagram account.
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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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CheatSheet | MATPLOTLIB
Matplotlib is a plotting library in Python for creating two and three-dimensional plots. All plotting is done with respect to x and y axes. To download the cheatsheet, please login below and follow our Facebook Page.
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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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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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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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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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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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