Tag

deep learning

Applied Natural Language Processing

From Real-World Natural Language Processing by Masato Hagiwara


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A New Approach to Deep Learning

From Probabilistic Deep Learning with Python by Oliver Dürr, Beate Sick, and Elvis Murina


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The Computer Vision Pipeline, Part 5: Classifier learning algorithms and conclusion

From Deep Learning for Vision Systems by Mohamed Elgendy

Neural Network Architectures

From Probabilistic Deep Learning with Python by Oliver Dürr, Beate Sick, and Elvis Murina

This article dives into neural network architectures and how get started implementing and using them.

The Computer Vision Pipeline, Part 4: feature extraction

From Deep Learning for Vision Systems by Mohamed Elgendy

In this part, we will take a look at feature extraction—a core component of the computer vision pipeline.

The Computer Vision Pipeline, Part 3: image preprocessing

From Deep Learning for Vision Systems by Mohamed Elgendy

In this part, we will delve into image preprocessing for computer vision systems.

Want to Learn Machine Learning Inside Out?

From Grokking Machine Learning by Luis G. Serrano


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Fun & Games

Six Questions for Kevin Ferguson, co-author of Deep Learning and the Game of Go.

Kevin Ferguson and Max Pumperla are deep learning specialists skilled in distributed systems and data science. Together, they built the open source bot BetaGo. They also both count Max, the hero of the movie Pi, as a major influence. “He’s a talented mathematician who slowly loses his mind over the stock market and has an intense relationship with his power tools. That’s essentially my short bio,” says Pumperla.

The Computer Vision Pipeline, Part 2: input images

From Deep Learning for Vision Systems by Mohamed Elgendy

In this part, we will discuss the input images for computer vision systems.

Tidying, Manipulating, and Plotting Data with the tidyverse

From Machine Learning with R, tidyverse, and mlr by Hefin Rhys

This article covers:

• What the tidyverse is
• What’s meant by tidy data
• How to install and load the tidyverse
• How to use the tibble, dplyr, ggplot2 and tidyr packages of the tidyverse

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