My WordPress Blog
My WordPress Blog
Overview of template type checking Just as TypeScript catches type errors in your code, Angular checks the expressions and bindings within the templates of your application and can report any type errors it finds. Angular currently has three modes of doing this, depending on the value of the fullTemplateTypeCheck and strictTemplates flags in the TypeScript configuration file. Basic mode In […]
In this chapter, we will be focus on the network we will have to learn from known set of points called x and f(x). A single hidden layer will build this simple network. The code for the explanation of hidden layers of perceptron is as shown below − Output Following is the representation of function […]
Multi-Layer perceptron defines the most complicated architecture of artificial neural networks. It is substantially formed from multiple layers of perceptron. The diagrammatic representation of multi-layer perceptron learning is as shown below − MLP networks are usually used for supervised learning format. A typical learning algorithm for MLP networks is also called back propagation’s algorithm. Now, […]
The following are metadata errors you may encounter, with explanations and suggested corrections. Expression form not supportedReference to a local (non-exported) symbolOnly initialized variables and constantsReference to a non-exported classReference to a non-exported functionFunction calls are not supportedDestructured variable or constant not supportedCould not resolve typeName expectedUnsupported enum member nameTagged template expressions are not supportedSymbol […]
Here, we will focus on MetaGraph formation in TensorFlow. This will help us understand export module in TensorFlow. The MetaGraph contains the basic information, which is required to train, perform evaluation, or run inference on a previously trained graph. Following is the code snippet for the same − One of the typical usage model for […]
This chapter will focus on how to get started with distributed TensorFlow. The aim is to help developers understand the basic distributed TF concepts that are reoccurring, such as TF servers. We will use the Jupyter Notebook for evaluating distributed TensorFlow. The implementation of distributed computing with TensorFlow is mentioned below − Step 1 − Import […]
When you use ahead-of-time compilation (AOT), you can control how your application is compiled by specifying template compiler options in the TypeScript configuration file. The template options object, angularCompilerOptions, is a sibling to the compilerOptions object that supplies standard options to the TypeScript compiler.tsconfig.json Configuration inheritance with extends Like the TypeScript compiler, the Angular AOT compiler also supports extends in the angularCompilerOptions section of the TypeScript […]
Keras is compact, easy to learn, high-level Python library run on top of TensorFlow framework. It is made with focus of understanding deep learning techniques, such as creating layers for neural networks maintaining the concepts of shapes and mathematical details. The creation of freamework can be of the following two types − Consider the following […]
In this chapter, we will focus on the difference between CNN and RNN − CNN RNN It is suitable for spatial data such as images. RNN is suitable for temporal data, also called sequential data. CNN is considered to be more powerful than RNN. RNN includes less feature compatibility when compared to CNN. This network […]
TFLearn can be defined as a modular and transparent deep learning aspect used in TensorFlow framework. The main motive of TFLearn is to provide a higher level API to TensorFlow for facilitating and showing up new experiments. Consider the following important features of TFLearn − Install TFLearn by executing the following command − pip install […]