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Say, the dataset is of 30 activities with varied share percentage. This is essential so that the machine learning algorithm is not biased towards any one class. One of the key things when working with data is to ensure that all classes are of approximately equal size. We will use these variables during machine learning analysis. By convention, small letter y acts as the set of labels and capital letter X acts as the set of features. We can drop this column and the remaining columns will be our features. In the remaining columns, subject is of no specific use for our machine learning application as we want to explore the activity and not who performed it. We see there are columns with the last column as Activity which will act as our label. We can use the head 5 method to get a glimpse of the first 5 rows of the training data. We print the output and see that the output is False meaning there are no null values. We must ensure that the dataset does not have any null values. There are rows and columns in the training dataset and rows and columns in the testing dataset.
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It results in the output as rows, columns. We use shape method to find the size of the dataset. This changes the backend for matplotlib to the Jupyter notebook as a result of which, all plots will now show up inline in the Jupyter notebook itself. There are a number of repositories that we will need in this project. This is from where I found the dataset for this project. I worked on this project as a Jupyter notebook which is available in my Activity Recognition using Machine Learning repo.
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Having gained some experience since that day, I believe today I can apply my machine learning knowledge to recognise activities now.įor the dataset, I selected the training. And even though implementation seemed a far-fetched goal at that time, I was intrigued by the application. One of the papers I discovered initially, involved using Machine Learning to classify activities. BuddyPress Activity Tags doesn't work with singleWhen I first began to explore machine learning, I read numerous articles and research papers. This plugin gets tags from each new blog posts activity and shows the most commonly used. Since this plugin allows you to monitor all activity sitewide, it will be very easy to quickly locate spam blogs and their BuddyPress Activity tab is used to output a list of sitewide, member or member's friends activity. Displays user logins, new comments and new posts as links. It provides an activity-o-meter on the user's Network plugin to display sitewide blog activity. The weight for each value is adjustable by an administrator.
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The User Activity module calculates an activity index based on a user's logins, page impressions, created nodes and comments. Bring all your activity on the web into Drupal.Īctivity Stream builds a lifestream for you by aggregating your social activities all in one place. The activity feed displays stories both when users like content on your Show your posts activity using a little progress image.
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You will need to download the The FaceBook Activity Feed Widget for WordPress displays the most interesting recent activity taking place on your web site based on feedback from Facebook users. With further image processing techniques, the output produced by this script can be refined and This system incorporates motion detection, face detection and face recognition module.Īfter that it emails the unrecognized faces and also makes a video clip. This file helps identify the presence of a human face, hand or any other body part by identifying and marking skin-like pixels within a given image. This demo shows some examples for image pre-processing before the recognition stage. Simple tutorial on pattern recognition using back propagation neural networks. This example come with a GUI with a trained network for handwritting recognition. You can use This demo shows the recognition stage for the character recognition. The voice recognition system can listen for specific phrases, or it can listen for general dictation.
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How to use the speech module to use speech recognition and text-to-speech in Windows XP or Vista. Humans can easily do it much easier than read twisted text and bots can't do it at all and never will.