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Browsing Category: Tensorflow Keras

Python Tensorflow Keras Unsupervised Learning

Autoencoder Implementation on Tensorflow

Autoencoders are an unsupervised learning technique in which we leverage neural networks for the task of representation learningWith the new Tensorflow API, it has become …

Python Tensorflow Keras

Feature Map Visualization Using Tensorflow Keras.

It is a good idea to visualize the feature maps for a specific input image in order to to understand what features of the …

Python Tensorflow Keras

Sentimental Analysis Using Tensorflow Keras.

Recurrent Neural Network (RNN) model has been very useful to processing sequential data. Tensorflow Keras is a great platform to implement RNN as the …

Python Tensorflow Keras

Time Series Forecasting using Tensorflow Keras

Recurrent Neural Network (RNN) model has been very useful to predict time series data.. Training on Tensorflow Keras is a great platform to implement …

Machine Learning Python Tensorflow Keras

Comparing Cross Entropy and KL Divergence Loss

Entropy is the number of bits required to transmit a randomly selected event from a probability distribution. A skewed distribution has a low entropy, whereas …

Machine Learning Python Tensorflow Keras

Comparing Pre-trained ResNet and MobileNet

Resnet and Mobilenet are the popular pre-trained models for computer visions. Renet is more accurate, while Mobilenet is much smaller in size. In this …

Machine Learning Python Tensorflow Keras

Network Compression with Depthwise Separable Convolution

One way to achieve network compression is using depthwise separable convolution. Depthwise separable convolution is used in many pre-trained neural networks such as MobileNet, …