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Keras Articles
Found 29 articles
Building an Auxiliary GAN using Keras and Tensorflow
Generative Adversarial Networks (GANs) which can be built using Keras and Tensorflow have revolutionized the field of artificial intelligence by enabling the generation of realistic and high-quality synthetic data. In this article, we delve into the world of GANs and explore the concept of an Auxiliary GAN. With the powerful combination of Keras and TensorFlow, we demonstrate how to construct an Auxiliary GAN that incorporates additional information to enhance the generation process. Understanding GANs Before diving into Auxiliary GANs, it's essential to understand the basics of GANs. GANs are composed of two neural networks: a generator and a ...
Read MoreHow to create Models in Keras?
In this article, we are going to learn about how to create Models in Keras Introduction Keras is an open-source library in Python which provides APIs for building Artificial Neural Network Models with great flexibility. Modelling in Keras can be done either using the Functional API or the Keras Sequential Model. Keras module is also available under the popular Tensorflow Library. Latest version and installation The latest version of keras as of writing this article is 2.1.0. Keras can be installed from PyPI repository using pip. Advantages of Keras for Modelling Keras is used for fast implementation due to ...
Read MoreDifference between TensorFlow and Keras
In this article, you will understand the significant differences between Tensorflow and Keras libraries.TensorFlowTensorFlow is an open-source end-to-end platform to build machine learning applications. It was developed by researchers and developers at Google Brain. Let us now see the features of TensorFlow − Build and Train models easily − TensorFlow offers multiple levels of abstraction to make it quick for you to choose the correct one. Build and train models by using the high-level Keras API, which makes beginning with TensorFlow and machine learning easy. Eager execution lets immediate iteration and intuitive debugging. For large ML training tasks, use the ...
Read MoreHow can Tensorflow Hub be used to fine-tune learning models?
TensorFlow Hub is a repository that contains trained machine learning models. These models are ready to be fine-tuned and deployed anywhere. The trained models such as BERT and Faster R-CNN can be reused with a few lines of code. It is an open-repository, which means it can be used and modified by anyone.The tfhub.dev repository contains many pre-trained models. Some of them include text embeddings, image classification models, TF.js/TFLite models and so on.It can be installed using the below code:!pip install --upgrade tensorflow_hubIt can be imported into the working environment as shown in the below code:import tensorflow_hub as hub
Read MoreHow can a customized model be pre-trained?
A sequential model can be built using Keras Sequential API that is used to work with plain stack of layers. Here every layer has exactly one input tensor and one output tensor.A pre-trained model can be used as the base model on the specific dataset. This saves the time and resources of having to train the model again on the specific dataset.A pre-trained model is a saved network which would be previously trained on a large dataset. This large dataset would be a large-scale image-classification task. A pre-trained model can be used as it is or it can be customized ...
Read MoreHow can Tensorflow be used to vectorise the text data associated with stackoverflow question dataset using Python?
Tensorflow is a machine learning framework that is provided by Google. It is an open-source framework used in conjunction with Python to implement algorithms, deep learning applications, and much more. It is used in research and for production purposes. It has optimization techniques that help in performing complicated mathematical operations quickly.This is because it uses NumPy and multi-dimensional arrays. These multi-dimensional arrays are also known as ‘tensors’. The framework supports working with deep neural networks. It is highly scalable and comes with many popular datasets. It uses GPU computation and automates the management of resources. It comes with multitude of ...
Read MoreHow can Tensorflow be used to find the state of preprocessing layer in dataset using Python?
Tensorflow is a machine learning framework that is provided by Google. It is an open-source framework used in conjunction with Python to implement algorithms, deep learning applications, and much more. It is used in research and for production purposes. It has optimization techniques that help in performing complicated mathematical operations quickly.This is because it uses NumPy and multi-dimensional arrays. These multi-dimensional arrays are also known as ‘tensors’. The framework supports working with a deep neural network. It is highly scalable and comes with many popular datasets. It uses GPU computation and automates the management of resources. It comes with multitude ...
Read MoreHow can Tensorflow be used to prepare the dataset with stackoverflow questions using Python?
Tensorflow is a machine learning framework that is provided by Google. It is an open-source framework used in conjunction with Python to implement algorithms, deep learning applications and much more. It is used in research and for production purposes.The ‘tensorflow’ package can be installed on Windows using the below line of code −pip install tensorflowTensor is a data structure used in TensorFlow. It helps connect edges in a flow diagram. This flow diagram is known as the ‘Data flow graph’. Tensors are nothing but multidimensional array or a list. We are using the Google Colaboratory to run the below code. ...
Read MoreHow can Tensorflow be used to load the dataset which contains stackoverflow questions using Python?
Tensorflow is a machine learning framework that is provided by Google. It is an open-source framework used in conjunction with Python to implement algorithms, deep learning applications, and much more. It is used in research and for production purposes. It has optimization techniques that help in performing complicated mathematical operations quickly.This is because it uses NumPy and multi-dimensional arrays. These multi-dimensional arrays are also known as ‘tensors’. The framework supports working with a deep neural networks. It is highly scalable and comes with many popular datasets. It uses GPU computation and automates the management of resources. It comes with multitude ...
Read MoreHow can Tensorflow be used to explore the dataset and see a sample file from the stackoverflow question dataset using Python?
Tensorflow is a machine learning framework that is provided by Google. It is an open-source framework used in conjunction with Python to implement algorithms, deep learning applications and much more. It is used in research and for production purposes.The ‘tensorflow’ package can be installed on Windows using the below line of code −pip install tensorflowKeras was developed as a part of the research for the project ONEIROS (Open-ended Neuro-Electronic Intelligent Robot Operating System). Keras is a deep learning API, which is written in Python. It is a high-level API that has a productive interface that helps solve machine learning problems. ...
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