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The Node.js Zlib module is used to provide compression and decompression (zip and unzip) functionalities. It is implemented using Gzip and deflate/inflate. The zlib module can be accessed using: Compressing and decompressing a file can be done by piping the source stream data into a destination stream through zlib stream. Node.js ZLIB Example: Compress File […]
The Node.js Query String provides methods to deal with query string. It can be used to convert query string into JSON object and vice-versa. To use query string module, you need to use require(‘querystring’). Node.js Query String Methods The Node.js Query String utility has four methods. The two important methods are given below. Method Description querystring.parse(str[, […]
The Node.js StringDecoder is used to decode buffer into string. It is similar to buffer.toString() but provides extra support to UTF. You need to use require(‘string_decoder’) to use StringDecoder module. Node.js StringDecoder Methods StringDecoder class has two methods only. Method Description decoder.write(buffer) It is used to return the decoded string. decoder.end() It is used to […]
The Node.js path module is used to handle and transform files paths. This module can be imported by using the following syntax: Syntax: Node.js Path Methods Let’s see the list of methods used in path module: Index Method Description 1. path.normalize(p) It is used to normalize a string path, taking care of ‘..’ and ‘.’ […]
In Node.js, file I/O is provided by simple wrappers around standard POSIX functions. Node File System (fs) module can be imported using following syntax: Syntax: Node.js FS Reading File Every method in fs module has synchronous and asynchronous forms. Asynchronous methods take a last parameter as completion function callback. Asynchronous method is preferred over synchronous […]
Streams are the objects that facilitate you to read data from a source and write data to a destination. There are four types of streams in Node.js: Each type of stream is an Event emitter instance and throws several events at different times. Following are some commonly used events: Node.js Reading from stream Create a […]
AutoKeras refers to an AutoML system based on Keras. It is developed by DATA Lab at Texas A&M University. The purpose of AutoKeras is to make machine learning accessible for everyone. It provides high-level end-to-end APIs such as ImageClassifier or TextClassifier to solve machine learning problems in a few lines, as well as flexible building […]
Keras comes packaged with TensorFlow 2 as tensorflow.keras. However, to start using Keras, simply install TensorFlow 2. Keras/TensorFlow is compatible with: Python 3.5–3.8 Ubuntu 16.04 or later Windows 7 or later macOS 10.12.6 (Sierra) or later.
Keras has built-in industry-strength support for multi-GPU training and distributed multi-worker training, via the tf.distribute API. However, if you have multiple GPUs on your machine, you can train your model on all of them by: Firstly, creating a tf.distribute.MirroredStrategy object. Secondly, creating and compiling your model inside the strategy’s scope. Lastly, calling fit() and evaluate() […]
Keras Tuner is an easy-to-use, scalable hyperparameter optimization framework that solves the pain points of hyperparameter search. In this, you can easily configure your search space with a define-by-run syntax, then leverage one of the available search algorithms for finding the best hyperparameter values for your models. Further, Keras Tuner comes with Bayesian Optimization, Hyperband, […]