Many machine learning models perform better when input variables are carefully transformed or scaled prior to modeling. It is convenient,…

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## Data Preparation for Machine Learning (7-Day Mini-Course)

Data preparation involves transforming raw data into a form that is more appropriate for modeling. Preparing data may be the…

Continue Reading## How to Use StandardScaler and MinMaxScaler Transforms in Python

Many machine learning algorithms perform better when numerical input variables are scaled to a standard range. This includes algorithms that…

Continue Reading## How to Use Polynomial Feature Transforms for Machine Learning

Often, the input features for a predictive modeling task interact in unexpected and often nonlinear ways. These interactions can be…

Continue Reading## How to Scale Data With Outliers for Machine Learning

Last Updated on May 27, 2020Many machine learning algorithms perform better when numerical input variables are scaled to a standard…

Continue Reading## How to Use Discretization Transforms for Machine Learning

Numerical input variables may have a highly skewed or non-standard distribution. This could be caused by outliers in the data,…

Continue Reading## Linear Discriminant Analysis for Dimensionality Reduction in Python

Last Updated on May 14, 2020Reducing the number of input variables for a predictive model is referred to as dimensionality…

Continue Reading## Singular Value Decomposition for Dimensionality Reduction in Python

Reducing the number of input variables for a predictive model is referred to as dimensionality reduction. Fewer input variables can…

Continue Reading## Principal Component Analysis for Dimensionality Reduction in Python

Reducing the number of input variables for a predictive model is referred to as dimensionality reduction. Fewer input variables can…

Continue Reading## How to Choose a Feature Selection Method For Machine Learning

Last Updated on November 28, 2019Feature selection is the process of reducing the number of input variables when developing a…

Continue Reading## How to Connect Model Input Data With Predictions for Machine Learning

Fitting a model to a training dataset is so easy today with libraries like scikit-learn. A model can be fit…

Continue Reading## How to Perform Feature Selection with Categorical Data

Feature selection is the process of identifying and selecting a subset of input features that are most relevant to the…

Continue Reading## 3 Ways to Encode Categorical Variables for Deep Learning

Machine learning and deep learning models, like those in Keras, require all input and output variables to be numeric. This…

Continue Reading## Attention in Neural Networks

Let’s look at another example, “Post photos in your Dropbox folder to Instagram”. Compared to the previous one, here “Instagram”…

Continue Reading## Uncovering what neural nets “see” with FlashTorch

The first feature visualisation technique I implemented is saliency maps. We’re going to look at it in more detail below,…

Continue Reading## AI For SEA Traffic Management: Modeling (Part 2/2)

Peaceful traffic near Angkor temples, CambodiaAI For SEA Traffic Management: Modeling (Part 2/2)Kilian TepBlockedUnblockFollowFollowingJun 17Also read: AI For SEA Traffic Management: Feature…

Continue Reading## Build a Modern, Customized File Uploading User Interface in React with Plain CSS

Or which files have already been uploaded?In a previous tutorial (you can find it if you search my posts), I…

Continue Reading## Introduction to Multilayer Neural Networks with TensorFlow’s Keras API

Introduction to Multilayer Neural Networks with TensorFlow’s Keras APILorraine LiBlockedUnblockFollowFollowingJun 11Learn how to build and train a multilayer perceptron using TensorFlow’s…

Continue Reading## An Overview of Deep Learning Based Clustering Techniques

An Overview of Deep Learning Based Clustering TechniquesDivam GuptaBlockedUnblockFollowFollowingMar 7This post gives an overview of various deep learning based clustering…

Continue Reading## Implementing a Simple Auto-Encoder in Tensorflow

Peele using DeepFake to forge a video of Obama — Source: BuzzFeed, YouTubeImplementing a Simple Auto-Encoder in TensorflowEdoardo BarpBlockedUnblockFollowFollowingJun 7Generative Adversarial Networks…

Continue Reading## Parallelising your Python Code

So your friend suggests that you and they take turns digging…Let's say it takes you 100 minutes to finish this…

Continue Reading## Neural Machine Translation

Neural Machine TranslationA guide to Neural Machine Translation using an Encoder Decoder structure with attention. Includes a detailed tutorial using…

Continue Reading## Composable Reactive UI — Preview

Well, he only concerns events, so we need something more powerful:h is like a Swiss knife: it’s able to configure…

Continue Reading## An Introduction to Convolutional Neural Networks

A typical hidden layer in such a network might have 1024 nodes, so we’d have to train 150,528 x 1024…

Continue Reading## Math of Neural Networks — from scratch in Python

Math of Neural Networks — from scratch in PythonOmar AflakBlockedUnblockFollowFollowingNov 14, 2018Make your own machine learning library. Photo by Mathew Schwartz on UnsplashIn this post…

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