In the previous blogs, we have discussed the LSTM and GRU, in this blog we’ll discuss the Word Embedding. As per Wikipedia, word embedding: Word embedding is the collective name for a set of language modeling and feature learning techniques in natural language processing (NLP) where words or phrases from the vocabulary are mapped to…
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This blog is about the song which people have watched in 2018. This list is limited to only Hindi -Bollywood song. This list does not include the Album or single hit song. Strategy to prepare the list can be done in two way, 1st is based on the number of views where the video has…
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In previous blog, we discussed the LSTM and there are other variants of LSTM and one of them is called GRU. As per wikipedia GRU is: Gated recurrent units (GRUs) are a gating mechanism inĀ recurrent neural networks, introduced in 2014 by Kyunghyun Cho et al.[Their performance on polyphonic music modeling and speech signal modeling was…
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In the last two blogs, we discussed RNN and RNN example, in this blog we’ll discuss the LSTM. As per wikipedia LSTM is: Long short-term memory (LSTM) units are units of a recurrent neural network (RNN). An RNN composed of LSTM units is often called an LSTM network (or just LSTM). A common LSTM unit is composed of a cell, an input gate,…
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In the previous blog , we discussed about RNN and simple example using TensorFlow. In this blog, we’ll try to predict the time series using RNN. First let’s generate a time series data. Generate a Time series data for equation y=sin(t)+Ļµ Create a routine to generate the batch data using the time series equation Now…
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In the previous blog we discussed how to use the pre-trained model of CNN and in this blog, we’ll discuss the Recurrent Neural Network (RNN). Recurrent Neural Network Till 45th day we have discussed the networks are feed forward i.e. activation flows only in one direction from the input layer to output layer direction. Recurrent…
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In the previous blog, we created a simple CNN model and tested using MNIST data, in this blog we’ll perform Classification using Inception V3 pre-trained model. We’ll download the Inception V3 pre-trained model from here. And use the name of the class from this file. You can find the detail about Inception V3 here. Architecture…
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In the previous blogs we have discussed the DNN and how to use pre-trained model for training, in this blog, we’ll discuss Convolutional Neural Networks ( CNN). As per the Wikipedia: In deep learning, a convolutional neural network (CNN, or ConvNet) is a class of deep neural networks, most commonly applied to analyzing visual imagery. Convolutional networks were inspired by biological processes[4] in that the…
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In the previous blog, we trained the layers to detect the five type of cloths using the MNIST fashion data, in this blog, we’ll reuse pre-trained layers to create a new model to detect the class 5-9. This process of reusing the pre-trained layers to create a model is called Transfer Learning. Let’s create a…
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In the previous blog we finished the basics of the Deep Neural network using the TensorFlow and in this blog, we’ll implement the DNN Basic classification using TensorFlow. We’ll use the MNIST Fashion data and we’ll train the model to predict the first 5 types of cloths. Let’s use library of TensorFlow to get the…
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