Tensorflow.js tf.grads() Function Last Updated : 21 May, 2021 Comments Improve Suggest changes Like Article Like Report Tensorflow.js is an open-source library developed by Google for running machine learning models and deep learning neural networks in the browser or node environment. It also helps the developers to develop ML models in JavaScript language and can use ML directly in the browser or in Node.js. The tf.grads() function takes a function f(x) and return a function gx Syntax: tf.grads (f) Parameters: f: This is the given function for which gradients are calculated. Return Value: It returns an array. Example 1: JavaScript // Importing the @tensorflow/tjs library const tf=require("@tensorflow/tfjs") const f = (a, b) => b.add(a); // Grad function is used const g = tf.grads(f); // Tensor is declared const a = tf.tensor1d([5, 6]); const b = tf.tensor1d([-10, -20]); // Variables are defined const [gfg1] = g([b, a]); // Variable is printed gfg1.print(); Output: Tensor [1, 1] Example 2: JavaScript // Importing the @tensorflow/tfjs library const tf=require("@tensorflow/tfjs") const f = (a) => a.mul(8); // Grad function is used const g = tf.grads(f); // Tensor is declared const a = tf.tensor1d([50, 60]); // Variables are defined const [gfg1] = g([a]); // Variable is printed gfg1.print(); Output: Tensor [8, 8] Reference: https://js.tensorflow.org/api/latest/#grads Comment More infoAdvertise with us Next Article Tensorflow.js tf.customGrad() Function D dheerchanana2002 Follow Improve Article Tags : JavaScript Web Technologies Tensorflow.js Similar Reads Introduction To TensorFlow.js TensorFlow.js is the popular library of JavaScript that helps us add machine learning functions to web applications. Tensor is the datatype which is used in the TensorFlow.Now, let us understand the TensorFlow.js and its components.What is TensorFlow.js?TensorFlow.js is the JavaScript library that a 4 min read Tensorflow.js Introduction TensorFlow.js brings machine learning to the browser and Node.js. It allows developers to build and run ML models directly in JavaScript and access AI for web applications. What is Tensorflow.js ?TensorFlow.js is a JavaScript library for training and deploying machine learning models on web applicat 2 min read Tensorflow.js TensorsTensorflow.js tf.tensor() FunctionTensorflow.js is an open-source library developed by Google for running machine learning models and deep learning neural networks in the browser or node environment. The .tensor() function is used to create a new tensor with the help of value, shape, and data type. Syntax :  tf.tensor( value, shape 3 min read Tensorflow.js tf.scalar() FunctionTensorflow.js is an open-source library developed by Google for running machine learning models and deep learning neural networks in the browser or node environment. The .scalar() function is used to create a scalar type of tensor means. A scalar is a zero-dimension array and is also called a rank-0 2 min read TenserFlow.js Tensors Creation Complete ReferenceTensorFlow.js is an open-source JavaScript library designed by Google to develop Machine Learning models and deep learning neural networks. Tensors are the core data structure that is the generalization of vectors and matrices. It is potentially higher in dimensions. The Creation is used to create t 1 min read Tensorflow.js tf.Tensor class .buffer() MethodTensorflow.js is an open-source library developed by Google for running machine learning models and deep learning neural networks in the browser or node environment. It also helps the developers to develop ML models in JavaScript language and can use ML directly in the browser or in Node.js. The tf. 1 min read Tensorflow.js tf.Tensor class .bufferSync() MethodTensorflow.js is an open-source library developed by Google for running machine learning models and deep learning neural networks in the browser or node environment. It also helps the developers to develop ML models in JavaScript language and can use ML directly in the browser or in Node.js. The tf. 1 min read TensorFlow.js Tensors Classes Complete ReferenceTensorFlow.js is an open-source JavaScript library designed by Google to develop Machine Learning models and deep learning neural networks. Tensor Class is used to show the main Tensor-related classes in TensorFlow.js and the methods we expose to them. tf.Tensor Class: Tensorflow.js tf.Tensor class 1 min read Tensorflow.js tf.booleanMaskAsync() FunctionTensorflow.js is an open-source library that is developed by Google for running machine learning models as well as deep learning neural networks in the browser or node environment. The .booleanMaskAsync() function is used to implement boolean mask to the stated input tensor. Syntax :  tf.booleanMas 2 min read Tensorflow.js tf.concat() FunctionTensorflow.js is an open-source library developed by Google for running machine learning models and deep learning neural networks in the browser or node environment. The tf.concat() function is used to concatenate the list of specified Tensors along the given axis. Syntax: tf.concat (tensors, axis)P 2 min read TensorFlow.js Tensors Transformations Complete ReferenceTensorFlow.js is an open-source JavaScript library designed by Google to develop Machine Learning models and deep learning neural networks. The tensor transformation is used to describe some common Tensor transformations for reshaping and type-casting. TensorFlow.js Tensors Transformations Methods: 1 min read Tensorflow.js tf.booleanMaskAsync() FunctionTensorflow.js is an open-source library that is developed by Google for running machine learning models as well as deep learning neural networks in the browser or node environment. The .booleanMaskAsync() function is used to implement boolean mask to the stated input tensor. Syntax :  tf.booleanMas 2 min read Tensorflow.js tf.concat() FunctionTensorflow.js is an open-source library developed by Google for running machine learning models and deep learning neural networks in the browser or node environment. The tf.concat() function is used to concatenate the list of specified Tensors along the given axis. Syntax: tf.concat (tensors, axis)P 2 min read TensorFlow.js Slicing and Joining Complete ReferenceTensorFlow.js is an open-source JavaScript library designed by Google to develop Machine Learning models and deep learning neural networks. The Tensor Slicing and Joining are used to slice or extract parts of a tensor or join multiple tensors together. TensorFlow.js Slicing and Joining functions: Te 1 min read Tensorflow.js tf.einsum() FunctionTensorflow.js is an open-source library that is being developed by Google for running machine learning models as well as deep learning neural networks in the browser or node environment. The .einsum () function is used to Tensor contraction over specified indices and outer product. Syntax : tf.eins 3 min read Tensorflow.js tf.multinomial() FunctionTensorflow.js is an open-source library that is developed by Google for running machine learning models as well as deep learning neural networks in the browser or node environment. The .multinomial() function is used to generate a tf.Tensor along with inputs that are dragged out of a multinomial dis 2 min read TensorFlow.js Tensor Random Complete ReferenceTensorFlow.js is an open-source JavaScript library designed by Google to develop Machine Learning models and deep learning neural networks. TensorFlow.js Tensor Random functions: TensorFlow.js tf.multinomial() FunctionTensorFlow.js tf.rand() FunctionTensorFlow.js tf.randomGamma() FunctionTensorFlow. 1 min read Tensorflow.js ModelsTensorflow.js tf.sequential() FunctionWhen you want to create a model which does not have multiple input and output and it will be developed layer by layer then we will go for a sequential model of deep learning. Basically there two types of models functional and sequential model. So in this article, we are going to see the Sequential m 2 min read Tensorflow.js tf.model() FunctionTensorflow.js is an open-source library that is developed by Google for running machine learning models as well as deep learning neural networks in the browser or node environment. The tf.model() function is used to create a model which contains layers and layers that are provided in form of input a 2 min read Tensorflow.js tf.input() FunctionThe models in deep learning are collections of connected Layers which can be trained, evaluate, and can be used to predict something. To perform this operation you need to instantiate an input to the models. In this post, We are going to know about how the input factory function works. The tf.input( 2 min read Tensorflow.js tf.loadGraphModel() FunctionTensorflow.js is an open-source library developed by Google for running machine learning models as well as deep learning neural networks in the browser or node environment. The .loadGraphModel() function is used to Load a graph model given a URL to the model definition. Syntax: tf.loadGraphModel (mo 2 min read Tensorflow.js tf.io.http() FunctionTensorflow.js is an open-source library that is developed by Google for running machine learning models as well as deep learning neural networks in the browser or node environment. The .io.http() function is used to generate an IOHandler subset which transmits model artifacts to the HTTP server. Mor 2 min read TensorFlow.js Models Loading Complete ReferenceTensorFlow.js is an open-source JavaScript library designed by Google to develop Machine Learning models and deep learning neural networks. TensorFlow.js Models Loading Functions: TensorFlow.js tf.loadGraphModel() FunctionTensorFlow.js tf.loadLayersModel() FunctionTensorFlow.js tf.io.browserDownload 1 min read Tensorflow.js tf.io.copyModel() FunctionTensorflow.js is an open-source library that is developed by Google for running machine learning models as well as deep learning neural networks in the browser or node environment. The copyModel() function is used to copy a model away from one URL towards a new one. Moreover, this method supports co 3 min read Tensorflow.js tf.io.listModels() FunctionTensorflow.js is an open-source library that is developed by Google for running machine learning models as well as deep learning neural networks in the browser or node environment. The .listModels() function is used to record each and every models accumulated in the registered repository means. More 2 min read Tensorflow.js tf.io.moveModel() FunctionTensorflow.js is an open-source library that is developed by Google for running machine learning models as well as deep learning neural networks in the browser or node environment. The .moveModel() function is used to move a model away from one URL towards a new one. Moreover, this method favors mov 3 min read TensorFlow.js Models Management Complete ReferenceTensorFlow.js is an open-source JavaScript library designed by Google to develop Machine Learning models and deep learning neural networks. TensorFlow.js Models Management Functions: TensorFlow.js tf.io.copyModel() FunctionTensorFlow.js tf.io.listModels() FunctionTensorFlow.js tf.io.moveModel() Func 1 min read Tensorflow.js tf.GraphModel ClassIntroduction: Tensorflow.js is an open-source library developed by Google for running machine learning models and deep learning neural networks in the browser or node environment. Tensorflow.js tf.GraphModel class is used to build an acyclic graph from SavedModel and made it inference execution. tf. 2 min read Tensorflow.js tf.GraphModel class .save() MethodIntroduction: Tensorflow.js is an open-source library that is developed by Google for running machine learning models as well as deep learning neural networks in the browser or node environment. The .save() function is used to save the structure and/or the weights of the stated GraphModel. Note: An 2 min read Tensorflow.js tf.GraphModel class .predict() MethodTensorflow.js is an open-source library that is developed by Google for running machine learning models as well as deep learning neural networks in the browser or node environment. The .predict() function is used to implement the implication in favor of input tensors. Syntax: predict(inputs, config? 2 min read Tensorflow.js tf.GraphModel class .execute() MethodTensorflow.js is an open-source library that is developed by Google for running machine learning models as well as deep learning neural networks in the browser or node environment. The .execute() method is used to implement implication in favor of the given model for the stated input tensors. Syntax 2 min read TensorFlow.js Models Classes Complete ReferenceTensorFlow.js is an open-source JavaScript library designed by Google to develop Machine Learning models and deep learning neural networks. TensorFlow.js Models Classes Functions: TensorFlow.js tf.Functional ClassTensorFlow.js tf.GraphModel ClassTensorFlow.js class .loadSync() MethodTensorFlow.js cl 1 min read Tensorflow.js LayersTensorflow.js tf.layers.elu() FunctionTensorflow.js is an open-source library developed by Google for running machine learning models and deep learning neural networks in the browser or node environment. It also helps the developers to develop ML models in JavaScript language and can use ML directly in the browser or Node.js. The tf.lay 2 min read Tensorflow.js tf.leakyRelu() FunctionTensorflow.js is an open-source library which is being developed by Google for running machine learning models as well as deep learning neural networks in the browser or node environment. The .leakyRelu() function is used to find the leaky rectified linear of the stated tensor input and is done elem 2 min read TensorFlow.js Layers Advanced Activation Complete ReferenceTensorFlow.js is an open-source JavaScript library designed by Google to develop Machine Learning models and deep learning neural networks. TensorFlow.js Layers Advance Activation Functions: TensorFlow.js tf.layers.elu() FunctionTensorFlow.js tf.layers.leakyReLU() FunctionTensorFlow.js tf.layers.pre 1 min read Tensorflow.js tf.layers.activation() FunctionIntroduction: Tensorflow.js is an open-source library developed by Google for running machine learning models and deep learning neural networks in the browser or node environment. Tensorflow.js tf.layers.activation() function is used to applied to function to all the element of our input layer . we 3 min read TensorFlow.js Layers Basic Complete ReferenceTensorFlow.js is an open-source JavaScript library designed by Google to develop Machine Learning models and deep learning neural networks. TensorFlow.js Layers Basic functions: TensorFlow.js tf.layers.activation() FunctionTensorFlow.js tf.layers.dense() FunctionTensorFlow.js tf.layers.dropout() Fun 1 min read Tensorflow.js tf.layers.conv1d() FunctionTensorflow.js is a javascript library developed by Google to run and train machine learning models in the browser or in Node.js. Tensorflow.js tf.layers.conv1d() function is used to create convolution layer. It is used to applied 1d convolution to the input data. The convolutional layer is used to m 4 min read TensorFlow.js Layers Convolutional Complete ReferenceTensorFlow.js is an open-source JavaScript library designed by Google to develop Machine Learning models and deep learning neural networks. TensorFlow.js Layers Convolutional functions: TensorFlow.js tf.layers.conv1d() FunctionTensorFlow.js tf.layers.conv2d() FunctionTensorFlow.js tf.layers.conv2dTr 1 min read Tensorflow.js tf.layers.add() FunctionTensorflow.js is an open-source library developed by Google for running machine learning models and deep learning neural networks in the browser or node environment. It also helps the developers to develop ML models in JavaScript language and can use ML directly in the browser or Node.js. The tf.lay 2 min read TensorFlow.js Layers Merge Complete ReferenceTensorFlow.js is an open-source JavaScript library designed by Google to develop Machine Learning models and deep learning neural networks. TensorFlow.js Layers Merge functions: TensorFlow.js tf.layers.add() FunctionTensorFlow.js tf.layers.average() FunctionTensorFlow.js tf.layers.concatenate() Func 1 min read Tensorflow.js tf.layers.globalAveragePooling1d() FunctionTensorflow.js is a Google-developed open-source toolkit for executing machine learning models and deep learning neural networks in the browser or on the node platform. It also enables developers to create machine learning models in JavaScript and utilize them directly in the browser or with Node.js. 2 min read TensorFlow.js Layers Pooling Complete ReferenceTensorFlow.js is an open-source JavaScript library designed by Google to develop Machine Learning models and deep learning neural networks. TensorFlow.js Layers Functions TensorFlow.js tf.layers.averagePooling1d() FunctionTensorFlow.js tf.layers.averagePooling2d() FunctionTensorFlow.js tf.layers.ave 1 min read TensorFlow.js Layers Noise Complete ReferenceTensorFlow.js is an open-source JavaScript library designed by Google to develop Machine Learning models and deep learning neural networks. TensorFlow.js Layers Recruitment Functions: TensorFlow.js tf.layers.alphaDropout() FunctionTensorFlow.js tf.layers.gaussianDropout() FunctionTensorFlow.js tf.la 1 min read Tensorflow.js tf.layers.bidirectional() FunctionTensorflow.js is an open-source library that is being developed by Google for running machine learning models as well as deep learning neural networks in the browser or node environment. The tf.layers.bidirectional function is a bidirectional wrapper for RNNs layer. Syntax: tf.layers.bidirectional( 2 min read Tensorflow.js tf.layers.timeDistributed() FunctionTensorflow.js is an open-source library developed by Google for running machine learning models and deep learning neural networks in the browser or node environment. The tf.layers.timeDistributed() function is used to apply the wrap of a layer to every temporal slice of a specified input. The given 3 min read TensorFlow.js Layers Classes Complete ReferenceTensorFlow.js is an open-source JavaScript library designed by Google to develop Machine Learning models and deep learning neural networks. TensorFlow.js Layers Classes functions: TensorFlow.js tf.layers.Layer() FunctionTensorFlow.js .apply() FunctionTensorflow.js tf.layers countParams() MethodTenso 1 min read Tensorflow.js tf.layers.zeroPadding2d() FunctionTensorflow.js is an open-source library developed by Google for running machine learning models and deep learning neural networks in the browser or node environment. The tf.layers.zeroPadding2d( ) function is used for adding rows and columns for zeros at the top, bottom, left, and right side of and 3 min read TensorFlow.js Layers Noise Complete ReferenceTensorFlow.js is an open-source JavaScript library designed by Google to develop Machine Learning models and deep learning neural networks. TensorFlow.js Layers Recruitment Functions: TensorFlow.js tf.layers.alphaDropout() FunctionTensorFlow.js tf.layers.gaussianDropout() FunctionTensorFlow.js tf.la 1 min read Tensorflow.js tf.layers.masking() FunctionTensorflow.js is an open-source library developed by Google for running machine learning models and deep learning neural networks in the browser or node environment. It also helps the developers to develop ML models in JavaScript language and can use ML directly in the browser or Node.js. The tf.lay 2 min read Tensorflow.js OperationsTensorFlow.js Operations Arithmetic Complete ReferenceTensorFlow.js is an open-source JavaScript library designed by Google to develop Machine Learning models and deep learning neural networks. TensorFlow.js Operations Arithmetic Functions: TensorFlow.js tf.add() FunctionTensorFlow.js tf.sub() FunctionTensorFlow.js tf.mul() FunctionTensorFlow.js tf.div 1 min read TensorFlow.js Operations Basic Math Complete ReferenceTensorFlow.js is an open-source JavaScript library designed by Google to develop Machine Learning models and deep learning neural networks. TensorFlow.js Operations Basic Math Functions: TensorFlow.js tf.abs() FunctionTensorFlow.js tf.acos() FunctionTensorFlow.js tf.acosh() FunctionTensorFlow.js tf. 1 min read TensorFlow.js Operations Matrices Complete ReferenceTensorFlow.js is an open-source JavaScript library designed by Google to develop Machine Learning models and deep learning neural networks. TensorFlow.js Operations Matrices Functions: TensorFlow.js tf.dot() FunctionTensorFlow.js tf.matMul() FunctionTensorFlow.js tf.norm() FunctionTensorFlow.js tf.o 1 min read TensorFlow.js Operations Convolution Complete ReferenceTensorFlow.js is an open-source JavaScript library designed by Google to develop Machine Learning models and deep learning neural networks. TensorFlow.js Operations Convolution Functions: TensorFlow.js tf.avgPool3d() FunctionTensorFlow.js tf.conv1d() FunctionTensorFlow.js tf.conv2d() FunctionTensorF 1 min read TensorFlow.js Operations Reduction Complete ReferenceTensorFlow.js is an open-source JavaScript library designed by Google to develop Machine Learning models and deep learning neural networks. TensorFlow.js Operations Reduction Functions: TensorFlow.js tf.all() FunctionTensorFlow.js tf.any() FunctionTensorFlow.js tf.argMax() FunctionTensorFlow.js tf.a 1 min read TensorFlow.js Operations Normalization Complete ReferenceTensorFlow.js is an open-source JavaScript library designed by Google to develop Machine Learning models and deep learning neural networks. TensorFlow.js Operations Normalization Functions: TensorFlow.js tf.batchNorm() FunctionTensorFlow.js tf.localResponseNormalization() FunctionTensorFlow.js tf.lo 1 min read TensorFlow.js Operations Images Complete ReferenceTensorFlow.js is an open-source JavaScript library designed by Google to develop Machine Learning models and deep learning neural networks. TensorFlow.js Operations Images Functions: TensorFlow.js tf.image.cropAndResize() FunctionTensorFlow.js tf.image.flipLeftRight() FunctionTensorFlow.js tf.image. 1 min read TensorFlow.js Operations Logical Complete ReferenceTensorFlow.js is an open-source JavaScript library designed by Google to develop Machine Learning models and deep learning neural networks. TensorFlow.js Operations Logical Functions: TensorFlow.js tf.equal() FunctionTensorFlow.js tf.greater() FunctionTensorFlow.js tf.greaterEqual() FunctionTensorFl 1 min read TensorFlow.js Operations Evaluation Complete ReferenceTensorFlow.js is an open-source JavaScript library designed by Google to develop Machine Learning models and deep learning neural networks. TensorFlow.js Operations Evaluation Functions: TensorFlow.js tf.confusionMatrix() FunctionTensorFlow.js tf.inTopKAsync() FunctionTensorFlow.js tf.topk() Functio 1 min read Tensorflow.js tf.cumsum() FunctionTensorFlow.js is a library for machine learning in JavaScript. It helps developers to develop ML models in JavaScript, and use ML directly in the browser or in Node.js. The tf.cumsum() function is used to compute the cumulative sum of a tf.Tensor along the specified axis. The meaning of exclusive cu 2 min read TensorFlow.js Operations Slicing and Joining Complete ReferenceTensorFlow.js is an open-source JavaScript library designed by Google to develop Machine Learning models and deep learning neural networks. TensorFlow.js Operations Slicing and Joining Functions: TensorFlow.js tf.gatherND() FunctionTensorFlow.js tf.meshgrid() FunctionTensorFlow.js tf.scatterND() Fun 1 min read TensorFlow.js Operations Spectral Complete ReferenceTensorFlow.js is an open-source JavaScript library designed by Google to develop Machine Learning models and deep learning neural networks. TensorFlow.js Operations Spectral Functions: TensorFlow.js tf.spectral.fft() FunctionTensorFlow.js tf.spectral.ifft() FunctionTensorFlow.js tf.spectral.irfft() 1 min read Tensorflow.js tf.unsortedSegmentSum() FunctionTensorflow.js is an open-source library that is developed by Google for running machine learning models as well as deep learning neural networks in the browser or node environment. The .unsortedSegmentSum() function is used to calculate the sum through the parts of a tf.Tensor. Syntax:  tf.unsorted 2 min read Tensorflow.js tf.movingAverage() FunctionIntroduction: Tensorflow.js is an open-source library that is developed by Google for running machine learning models as well as deep learning neural networks in the browser or node environment. The .movingAverage() function is used to determine the moving average of a variable. Note: In absence of 2 min read Tensorflow.js tf.dropout() FunctionTensorflow.js is an open-source library developed by Google for running machine learning models and deep learning neural networks in the browser or node environment. The tf.dropout() function is used to compute the dropout. You can read more about dropout from https://www.geeksforgeeks.org/dropout-i 2 min read TensorFlow.js Operations Signal Complete ReferenceTensorFlow.js is an open-source JavaScript library designed by Google to develop Machine Learning models and deep learning neural networks. TensorFlow.js Operations Signal Functions: TensorFlow.js tf.signal.frame() FunctionTensorFlow.js tf.signal.hammingWindow() FunctionTensorFlow.js tf.signal.hannW 1 min read Tensorflow.js tf.linalg.bandPart() FunctionTensorflow.js is an open-source library developed by Google for running machine learning models and deep learning neural networks in the browser or node environment. It also helps the developers to develop ML models in JavaScript language and can use ML directly in the browser or in Node.js. The tf. 2 min read Tensorflow.js tf.linalg.gramSchmidt() FunctionTensorflow.js is an open-source library developed by Google for running machine learning models and deep learning neural networks in the browser or node environment. The tf.linalg.gramSchmidt() function is used to orthogonalize the vectors using the Gram-Schimdt process. Syntax: tf.linalg.gramSchmid 1 min read Tensorflow.js tf.linalg.qr() FunctionTensorflow.js is an open-source library that is developed by Google for running machine learning models as well as deep learning neural networks in the browser or node environment. It also helps the developers to develop ML models in JavaScript language and can use ML directly in the browser or in N 2 min read TensorFlow.js Operations Sparse Complete ReferenceTensorFlow.js is an open-source JavaScript library designed by Google to develop Machine Learning models and deep learning neural networks. TensorFlow.js Operations Signal Functions: TensorFlow.js tf.sparseFillEmptyRows() FunctionTensorFlow.js tf.sparseReshape() FunctionTensorFlow.js tf.sparseSegmen 1 min read Tensorflow.js TrainingTensorflow.js tf.grad() FunctionTensorflow.js is an open-source library developed by Google for running machine learning models and deep learning neural networks in the browser or node environment. The tf.grad() function is used to return the gradient of the specified function f(x) with respect to x. Syntax:  tf.grad (f) Paramete 2 min read Tensorflow.js tf.grads() FunctionTensorflow.js is an open-source library developed by Google for running machine learning models and deep learning neural networks in the browser or node environment. It also helps the developers to develop ML models in JavaScript language and can use ML directly in the browser or in Node.js. The tf. 1 min read Tensorflow.js tf.customGrad() FunctionTensorflow.js is an open-source library developed by Google for running machine learning models and deep learning neural networks in the browser or node environment. The tf.customGrad() function is used to return the gradient of a specified custom function "f". Here the custom function gives {value: 3 min read TensorFlow.js Training Gradients Complete ReferenceTensorFlow.js is an open-source JavaScript library designed by Google to develop Machine Learning models and deep learning neural networks. TensorFlow.js Training Gradients Functions: TensorFlow.js tf.grad() FunctionTensorFlow.js tf.grads() FunctionTensorFlow.js tf.customGrad() FunctionTensorFlow.js 1 min read Tensorflow.js tf.train.sgd() FunctionTensorflow.js is an open-source library that is developed by Google for running machine learning models as well as deep learning neural networks in the browser or node environment. The .train.sgd() function is used to build a tf.SGDOptimizer which utilizes stochastic gradient descent. Syntax: tf.tra 1 min read Tensorflow.js tf.train.momentum() FunctionTensorflow.js is an open-source library developed by Google for running machine learning models and deep learning neural networks in the browser or node environment. The tf.train.momemtum() function is used to create a tf.MomentumOptimizer that uses momentum gradient decent algorithm. Syntax: tf.tr 2 min read Tensorflow.js tf.train.adagrad() FunctionTensorflow.js is an open-source library developed by Google for running machine learning models and deep learning neural networks in the browser or node environment. The tf.train.adagrad() function us used to create a tf.AdagradOptimizer that uses Adaptive Gradient Algorithm(adagrad). Syntax: tf.tr 2 min read TensorFlow.js Training Optimizers Complete ReferenceTensorFlow.js is an open-source JavaScript library designed by Google to develop Machine Learning models and deep learning neural networks. TensorFlow.js Training Optimizers Functions: TensorFlow.js tf.train.sgd() FunctionTensorFlow.js tf.train.momentum() FunctionTensorFlow.js tf.train.adagrad() Fun 1 min read Tensorflow.js tf.losses.absoluteDifference() FunctionTensorflow.js is an open-source library developed by Google for running machine learning models and deep learning neural networks in the browser or node environment. It also helps the developers to develop ML models in JavaScript language and can use ML directly in the browser or in Node.js. The Ten 2 min read Tensorflow.js tf.losses.computeWeightedLoss() FunctionTensorflow.js is an open-source library developed by Google for running machine learning models and deep learning neural networks in the browser or node environment. It also helps the developers to develop ML models in JavaScript language and can use ML directly in the browser or in Node.js. The Ten 2 min read Tensorflow.js tf.losses.cosineDistance() FunctionTensorflow.js is an open-source library developed by Google for running machine learning models and deep learning neural networks in the browser or node environment. The tf.losses.cosineDistance() function is used to Compute the cosine distance loss between two tensors. Syntax: tf.losses.cosineDista 2 min read TensorFlow.js Training Losses Complete ReferenceTensorFlow.js is an open-source JavaScript library designed by Google to develop Machine Learning models and deep learning neural networks. TensorFlow.js Training Losses Functions: TensorFlow.js tf.losses.absoluteDifference() FunctionTensorFlow.js tf.losses.computeWeightedLoss() FunctionTensorFlow.j 1 min read Tensorflow.js tf.train.Optimizer ClassTensorflow.js is an open-source library developed by Google for running machine learning models and deep learning neural networks in the browser or node environment. The tf.train.Optimizer() class is used to extend Serializable class. This tf.train.Optimizer() class contains three inbuilt functions 3 min read Tensorflow.js tf.train.Optimizer class .minimize() MethodTensorflow.js is an open-source library developed by Google for running machine learning models and deep learning neural networks in the browser or node environment. The .minimize() method executes the given function f() and tries to minimize the scalar output of f() by computing the gradients of y 3 min read TensorFlow.js Training Classes Complete ReferenceTensorFlow.js is an open-source JavaScript library designed by Google to develop Machine Learning models and deep learning neural networks. TensorFlow.js Training Classes Functions: TensorFlow.js tf.train.Optimizer ClassTensorFlow.js tf.train.Optimizer class .minimize() MethodTensorFlow.js tf.train. 1 min read Tensorflow.js PerformanceTensorflow.js tf.time() FunctionTensorflow.js is an open-source library that was developed by Google for running machine learning models as well as deep learning neural networks in the browser or node environment. The tf.time() function is used to execute the stated function, f() as well as return a promise in order that determine 2 min read Tensorflow.js tf.nextFrame() FunctionIntroduction: Tensorflow.js is an open-source library that is developed by Google for running machine learning models as well as deep learning neural networks in the browser or node environment. The .nextFrame() function is used to return a promise which determines at which a requestAnimationFrame 2 min read Tensorflow.js tf.profile() FunctionTensorflow.js is an open-source library developed by Google for running machine learning models and deep learning neural networks in the browser or node environment. It also helps the developers to develop ML models in JavaScript language and can use ML directly in the browser or in Node.js. The tf. 1 min read TensorFlow.js Performance Memory Complete ReferenceTensorFlow.js is an open-source JavaScript library designed by Google to develop Machine Learning models and deep learning neural networks. TensorFlow.js Performance Memory Functions: TensorFlow.js tf.tidy() FunctionTensorFlow.js tf.dispose() FunctionTensorFlow.js tf.keep() FunctionTensorFlow.js tf. 1 min read Tensorflow.js EnvironmentTensorflow.js tf.Environment ClassTensorflow.js is an open-source library developed by Google for running machine learning models and deep learning neural networks in the browser or node environment. The tf.Environment() class includes assessed flags and the registered platform. It is every time utilized like a global singleton and 3 min read Tensorflow.js tf.disposeVariables() FunctionTensorflow.js is an open-source library that is developed by Google for running machine learning models as well as deep learning neural networks in the browser or node environment. The .disposeVariables() function is used to dispose every single variable stored in the backend engine. Syntax: tf.disp 1 min read Tensorflow.js tf.enableDebugMode() FunctionTensorflow.js is an open-source library that is developed by Google for running machine learning models as well as deep learning neural networks in the browser or node environment. The .enableDebugMode() function is used to enable the debug mode that would register data regarding every single execut 2 min read Tensorflow.js tf.enableProdMode() FunctionTensorflow.js is an open-source library that is developed by Google for running machine learning models as well as deep learning neural networks in the browser or node environment. The .enableProdMode() function is used to enable the mode of production that deactivates the exactness restraints in su 2 min read Tensorflow.js tf.engine() FunctionTensorflow.js is an open-source library that is developed by Google for running machine learning models as well as deep learning neural networks in the browser or node environment. The .engine() function is used to return the global engine which saves the path of every single tensor as well as backe 2 min read Tensorflow.js tf.env() FunctionTensorflow.js is an open-source library that is developed by Google for running machine learning models as well as deep learning neural networks in the browser or node environment. The .env() function is used to return the present environment i.e. a global entity. Moreover, the environment object in 1 min read TensorFlow.js Environment Complete ReferenceTensorFlow.js is an open-source JavaScript library designed by Google to develop Machine Learning models and deep learning neural networks. TensorFlow.js Environment Functions TensorFlow.js tf.Environment ClassTensorFlow.js tf.disposeVariables() FunctionTensorFlow.js tf.enableDebugMode() FunctionTen 1 min read Tensorflow.js ConstraintsTensorflow.js tf.metrics.binaryAccuracy() FunctionTensorflow.js is an open-source library developed by Google for running machine learning models and deep learning neural networks in the browser or node environment. The tf.metrics.binaryAccuracy() function is used to calculate how often predictions match binary labels. And the function takes two te 2 min read Tensorflow.js tf.metrics.binaryCrossentropy() FunctionTensorflow.js is an open-source library developed by Google for running machine learning models as well as deep learning neural networks in the browser or node environment. The .metrics.binaryCrossentropy() function is binary crossentropy metric function which uses binary tensors and returns tf.Tens 1 min read Tensorflow.js tf.metrics.categoricalAccuracy() FunctionTensorflow.js is an open-source library developed by Google for running machine learning models and deep learning neural networks in the browser or node environment. The tf.metrics.categoricalAccuracy() function is used to return categorical accuracy between two tensor. It takes two tensor as a para 2 min read Tensorflow.js tf.metrics.categoricalCrossentropy() FunctionTensorflow.js is an open-source library developed by Google for running machine learning models and deep learning neural networks in the browser or node environment. It also helps the developers to develop ML models in JavaScript language and can use ML directly in the browser or in Node.js. The tf. 1 min read Tensorflow.js tf.metrics.cosineProximity() FunctionTensorflow.js is an open-source library developed by Google for running machine learning models and deep learning neural networks in the browser or node environment. It also helps the developers to develop ML models in JavaScript language and can use ML directly in the browser or in Node.js. The tf. 2 min read Tensorflow.js tf.metrics.meanAbsoluteError() FunctionTensorflow.js is an open-source library developed by Google for running machine learning models and deep learning neural networks in the browser or node environment. The tf.metrics.meanAbsoluteError() is used to calculate mean absolute error. The mean absolute error is defined as the mean of absolut 2 min read Tensorflow.js tf.metrics.meanAbsolutePercentageError() FunctionTensorflow.js is an open-source library developed by Google for running machine learning models as well as deep learning neural networks in the browser or node environment. The .metrics.meanAbsolutePercentageError() function is a loss or else a metric function i.e. mean absolute percentage error whi 2 min read Tensorflow.js tf.metrics.meanSquaredError() FunctionTensorflow.js is an open-source library developed by Google for running machine learning models and deep learning neural networks in the browser or node environment. The Tensorflow tf.metrics.meanSquaredError() function is a Loss or metric function used to  Computes the mean squared error between y_ 2 min read Tensorflow.js tf.metrics.precision() FunctionTensorflow.js is an open-source library developed by Google for running machine learning models as well as deep learning neural networks in the browser or node environment. The .metrics.precision() function is used to calculate the precision of the expectancy with reference to the names. Syntax:  t 2 min read Tensorflow.js tf.metrics.recall() FunctionTensorflow.js is an open-source library developed by Google for running machine learning models and deep learning neural networks in the browser or node environment. The tf.metrics.recall() function is used to compute the recall of the predictions with respect to the labels. 'Recall' is one of the m 2 min read Tensorflow.js tf.metrics.sparseCategoricalAccuracy() FunctionTensorflow.js is an open-source library developed by Google for running machine learning models as well as deep learning neural networks in the browser or node environment. The .metrics.sparseCategoricalAccuracy() function is sparse categorical accuracy metric function which uses indices and logits 1 min read TensorFlow.js Metrics Complete ReferenceTensorFlow.js is an open-source JavaScript library designed by Google to develop Machine Learning models and deep learning neural networks. Metrics functions are used to manipulate the matrices. TensorFlow.js Metrics functions: TensorFlow.js tf.metrics.binaryAccuracy() FunctionTensorFlow.js tf.metri 1 min read Like