State of Art Augmentations are written in a very clumsy way and it is not necessary you will find a version of it in Tensorflow. TensorPipe: A High performance and flexible data pipeline written in core TensorFlow.
Text augmentation techniques for phishing email detection. However, fraud email and phishing email occupy a small set of data when comparing to normal email.
In this article, we’ll go through all the major data augmentation methods for NLP that you can use to increase the size of your textual dataset and improve your model performance.
This blog is one of the masterpieces which will explain the actual/right meaning of Data Augmentation & its variations. In addition to that, the myths related to Data Augmentation are clarified in this blog.
So you think you don’t have enough data to do Machine Learning. Ask a beginner why ML is so difficult and you will most likely get an answer ... So you think you don't have enough data to do Machine Learning.
Data Augmentation in Medical Images. How to improve vision model performance by reshaping and resampling data
Enrich your train fold with a custom sampler inside an imblearn pipeline. I wouldn’t be able to write this article without the help of my colleagues and people from StackOverflow!
English is one of the languages which has lots of training data for translation while some language may not has enough data to train a machine translation model. Sennrich et al. used the back-translation method to generate more training data to improve translation model performance.
When it comes to small data sets, life can get complicated. In medicine, a data set can easily consist of less than 100 patients/rows. But in the other dimension it can become pretty large — easily over 3000 features.
Discussing the necessity of augmenting the images for CNN to improve the accuracy of our model using different augmenting techniques present in KERAS.
A effect and smart blog on image classification using fast. Let us download images from Google, Identify them using Image Classification Models and Export them for developing applications.
Data Augmentation is a technique in Deep Learning which helps in adding value to our base dataset by adding the gathered information.
An implementation with Keras. Whenever you build and train a model for a machine learning task, regardless of its being a classification or regression one.
CutMix: A new strategy for Data Augmentation. Get to know CutMix data augmentation strategy along with an overview of some other augmentations.
State of the art modeling with image data augmentation and management. Of the techniques we have covered here, this one is probably the least intuitive and closest to the modeling side of things.