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September 2, 2020

Pytorch Image Augmentation using Transforms.

PyTorchBrijesh0

The quality of the images will not be the same from each source. Some images might be of very high quality while others might be just plain bad. In such scenarios, we can blur the image. This helps make our deep learning model more robust. Transforms provide a class for randomly change the brightness, contrast, and saturation of an image.

August 23, 2020

Convert PASCAL dataset to TFRecord for object detection in TensorFlow

TensorFlowBrijesh0

Once you are done annotating your image dataset in the Pascal VOC format, you must convert your data into the TFRecord format. Because to use your own dataset in TensorFlow Object Detection API, you must convert it into the TFRecord file format.

August 13, 2020

Change the Learning Rate using Schedules API in Keras

KerasBrijesh0

The intuition behind slowly reducing the learning rate is that maybe during the initial steps of learning you can afford to take much bigger steps but then as learning approaches convergence then having a slower learning rate allows you to take smaller steps.

August 3, 2020

Convolutional Neural Network using Sequential model in PyTorch.

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How easy this looks compared to when we had to construct a model through the class way of doing it. Sequential class lives in the neural network package and this is a class that we are building by or we’re building an instance of this class by passing in other modules in a sequential.

July 10, 2020

Discretization, Binning, and Count in Column with Pandas.

PandasBrijesh0

For Data analysis continuous data is often discretized or separated into “bins”.Suppose you have a list of people and their age and you want to group them into discrete age buckets.

June 23, 2020

Plot Correlation Matrix and Heatmaps between columns using Pandas and Seaborn.

PandasBrijesh0

Using the correlation coefficient you can find out how these two variables are related and to what degree. Please note that this is only a part of the whole dataset.

June 16, 2020

Detect and Remove Outliers from Pandas DataFrame

PandasBrijesh0

Z-score re-scale and center(Normalize) the data and look for data points which are too far from zero(center). Data points far from zero will be treated as the outliers. In most of the cases, a threshold of 3 or -3 is used i.e if the Z-score value is greater than or less than 3 or -3 respectively, that data point will be identified as outliers.

June 9, 2020

How to Normalize(Scale, Standardize) Pandas DataFrame columns using Scikit-Learn?

PandasBrijesh0

Many machine learning models are designed with the assumption that each feature values close to zero or all features vary on comparable scales. The gradient-based model assumes standardized data.

May 26, 2020

Display Auto Size AlertDialog with ListView in Flutter

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AlertDialog has the ability to display different kinds of widgets. Here we will see the 3 different types of ListView to display the list in AlertDialog and how to set dialog width and height to fit actual items size.

May 22, 2020

Training RNN model with variable length sequences in Keras using RaggedTensor.

KerasTensorFlowBrijesh0

RaggedTensor is a new type of Tensor, it efficiently represents sequence data. It designed to handle text and other variable-length sequences. It native representation of sequences of varying shapes.

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