Machine Learning

7 years ago 0 92

Xavier Weight Initialization Technique in Neural Networks

Weight initialization is the most important step while training the neural network. If weights are high, it may lead ...

7 years ago 0 99

Deep Learning Machine Learning

Batch Normalization in Neural Networks in Deep Learning

Batch normalization (batchnorm) is a technique to improve performance and accuracy of a neural network. Many times, normalization ...

7 years ago 0 100

Deep Learning Machine Learning

Transfer Learning and Fine Tuning a model in Deep Learning

Transfer learning and fine-tuning terms are very similar in many ways and widely used almost interchangeably. Fine-tuning: Suppose ...

7 years ago 0 111

Deep Learning Machine Learning

Capsule Neural Networks: An enhancement of Convolutional Neural Networks (ConvNets vs CapsNets)

Capsule Neural Networks can be seen as an enhancement of Convolutional Neural Networks. In order to understand capsule ...

7 years ago 0 102

Deep Learning Machine Learning

Difference between Sigmoid and Softmax function in deep learning

Softmax function can be understood as a generalized version of a sigmoid function or an extension of a ...

7 years ago 0 115

Deep Learning Machine Learning Overfitting Regularization

Regularization Techniques used in Neural Networks in Deep Learning

Ideally, the neural networks should never underfit and overfit and maintain good generalization capabilities. For this purpose, we ...

7 years ago 0 101

Cross Validation Deep Learning Machine Learning

Hyperparameter Tuning in Neural Networks in Deep Learning

In order to minimize the loss and determine optimal values of weight and bias, we need to tune ...

7 years ago 0 87

Deep Learning Machine Learning

Global and Local Minima in Gradient Descent in Deep Learning

Task of a Gradient Descent optimizer is to find out optimal weights for the parameters. But sometimes, it ...

7 years ago 0 102

Deep Learning Machine Learning

Momentum and Adaptive Learning based Gradient Descent Optimizers: Adagrad and Adam

In my previous article on Gradient Descent Optimizers, we had discussed about three types of Gradient Descent algorithms: ...

7 years ago 0 102

Deep Learning Machine Learning Python TensorFlow

Implement a Linear Classification Model using TensorFlow Estimator

Lets see how can we perform linear classification using TensorFlow library in Python. We will use LinearClassifier function from ...

7 years ago 0 109

Deep Learning Machine Learning Python TensorFlow

Implement a simple Gradient Descent Optimizer in TensorFlow

Lets implement a simple Gradient Descent Optimizer in TensorFlow for a linear model. We will use GradientDescentOptimizer function present in ...

7 years ago 0 107

Deep Learning Machine Learning Python TensorFlow

Constants, Placeholders, Variables and Sessions in TensorFlow

In this article on TensorFlow, we will see how to build and run a graph taking simple examples ...

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