Backpropagation through time (BPTT) is a gradient-based technique for training certain types of recurrent neural networks. It can be used to train Elman networks. The algorithm was independently derived by numerous researchers.
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The forward propagation in an RNN makes a few assumptions: 1) We assume the hyperbolic tangent activation function for the hidden layer. 2) We assume that the output is discrete as if the RNN is used to predict words or...

NLP is a tool for structuring data in a way that AI systems can process that deals with language. NLP uses AI to 'read' through a document and extract key information.
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This clip is from the chapter "Recurrent Neural Networks"...

This video explains padding in convolutional neural networks.
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This clip is from the chapter "Convolutional Neural Networks" of the series "Fundamentals in Neural Networks".This section explains convolutional neural networks...

This video explains the optimization problem using the gradient descent algorithm.
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This clip is from the chapter "Artificial Neural Networks" of the series "Fundamentals in Neural Networks".This section explains artificial...

This video explains the cross-entropy function, which is designed under the assumption that the variable you are trying to predict is binary.
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This clip is from the chapter "Artificial Neural Networks" of the series...

This video explains the role of the activation function, which is an interesting phenomenon in the design of neural networks.
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This clip is from the chapter "Artificial Neural Networks" of the series "Fundamentals in Neural...

This video explains forward propagation and will dive deeper into the architecture of neural networks.
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This clip is from the chapter "Artificial Neural Networks" of the series "Fundamentals in Neural Networks".This section...

This video explains the need for taking up the course and introduces you to the author.
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This clip is from the chapter "Welcome" of the series "Fundamentals in Neural Networks".This section introduces you to the course and the...

You will learn how to create a sales dashboard from the sales dataset of an automotive company.

In this video, you will learn how to create a geospatial dashboard containing a dataset containing a digitized paper location from World War II.

This is a continuation of the previous chapter regarding advanced tableau charts, including horizontal and stacked bars, side-by-side bars, line and dual-line charts, and area charts. We will look at a Sankey diagram in detail.

In this video, you will learn about animating visualizations. You will learn to use the pre-attentive attribute of motion to make users understand the date of an underlying visualization.

Continuing on the examples of geospatial charts, we will use the places of worship in the US Excel sheet and create a map chart in layers.

After learning about spatial functions, we will try to apply the geospatial functions learned from the previous lesson. We will use the San Francisco Flight Excel file.

This video will explain spatial functions and how we can perform spatial analysis. We will also combine spatial files in other formats and read spatial files such as Shapefiles, MapInfo, TopoJSON, and so on.

In this video, we will look at the level of detail expression, which alters how specific or broad a visualization can be, the levels of granularity that it controls, and apply aggregations to the current visualization.

You will learn about numeric and automatic expressions that we currently have in our datasets. You will learn to use calculated fields to create new calculations and functions.

In this lesson, you will learn to use expressions and aggregation in Tableau, forming individual data into a cluster group on specific measurements.

In this video, we will understand spatial data, which provides us with a better understanding of populations, communities, or anything with geographical information and how it is affected by a variable.

Here, we will understand correlation, the statistical method of finding relationships between two or more variables, and create a scatter plot.

Let's learn about a chart that is instantly recognizable to data scientists and statisticians: the distribution chart.

This video will look at using numbers and tables in tabular form. We will look at the options of Tableau to classify data into tables or lists of values, similar to a spreadsheet.

We will look at the main interface for creating the data visualizations and analyses, the Tableau workspace.