AutoML for fast labeling with Kili Technology This tutorial is taken from our recipes. You can find an executable version of the Jupyter notebook on Github. In this tutorial, we will show how to use automated machine learning (AutoML) to accelerate labeling in Kili Technology. We will apply it in the context of text classification: … Continue reading AutoML for fast annotation
Video annotation is the process of labelling video clips. This is done to prepare it as a dataset for training deep learning (DL) and machine learning (ML) models. These pre-trained neural networks are then used for computer vision applications, such as automatic video classification tools. ML is a field of artificial intelligence (AI) research, which … Continue reading What is Video Annotation for Deep Learning
The dataset that you use to train your machine learning models can make or break the performance of your applications. For example, using a text dataset that contains loads of biased information can significantly decrease the accuracy of your machine learning model. This was what happened to Amazon's initial tests. They trained a machine learning … Continue reading How to Create a Dataset to Train Your Machine Learning Applications
Image annotation plays an important role in training a machine to automatically assign relevant metadata information to a digital picture. This metadata often includes captions, keywords, location markers, or any combination of these details. This process is required for creating datasets that are used to train the deep learning models of computer vision applications. Many … Continue reading What is Image Annotation in Deep Learning?
What is Text Annotation in Machine Learning? Simply put, text annotation in machine learning ( ML ) is the process of associating labels to a digital file or document and its content. This is an NLP method where different types of sentence structures are highlighted by various criteria. Because human language is quite complex, annotation … Continue reading What is Text Annotation in Machine Learning?
I'll give you four reasons. Labeled data is the missing brick to create an AI To make artificial intelligence you need three components: Computing power It is now widely available, easily scalable and relatively inexpensive with the cloud and GPU. And computing power is growing exponentially. On your iPhone you have more computing power than … Continue reading Why is annotation much more complicated than it seems?
Je vais vous donner quatre raisons. Première raison: le plus dur à trouver créer une IA, c’est la donnée annotée. Pour faire de l’intelligence artificielle on a besoin de 3 composantes: Puissance de calcul Elle est aujourd’hui largement disponible, facilement scalable et relativement pas cher avec le cloud et le GPU. Et la puissance de … Continue reading Pourquoi l’annotation est beaucoup plus compliquée qu’il n’y paraît ?
What is data annotation for image, text, voice, and video ? We all experience that artificial intelligence will transform our society; however, we do not know how or to what extent. Two things are certain: The subject, long confined to laboratories, is moving on to industrial applicationsAnd it's going to transform a lot of things … Continue reading Kili Technology; we industrialize annotation for machine learning
Et comprendre ce qu'est l'annotation de données image, texte, voix Nous expérimentons tous que l’intelligence artificielle va transformer notre société; en revanche, nous ne savons pas comment, ni dans quelle mesure. Deux choses sont certaines: Le sujet, longtemps circonscrit aux laboratoires, est en train de passer aux applications industriellesEt cela va transformer beaucoup de chose … Continue reading Kili Technology, industrialiser l’annotation pour le machine learning