Category: Deep Learning

Many of the times, after building a model we tend to visualize the accuracy and validation plots manually with Matplotlib (or any other) visualization library. But there is a better way to do it. We can easily visualize the plots using TensorBoard which provides a beautiful and interactive environment by default. In this article, you […] ...

Training Deep Neural Networks is time-consuming and difficult. Batch Normalization is a technique that can help to speed up the training of neural networks. In this article, you will get to know what Batch Normalization is and how it helps in training of deep neural networks. Difficulty in Training Deep Neural Networks Training very deep […] ...

In neural networks, the backpropagation algorithm is important to train the network. But it also raises another problem. That is the problem of vanishing gradients. In this article, we are going to dive into the topic of vanishing gradients in neural networks and why it is a problem while training. A Bit About Backpropagation The […] ...

Beginners often face difficulties when getting started with Deep Learning, even if they have some prior experience in Machine Learning. Setting up the environment is yet another pain point when starting deep learning. In this article, you are going to learn how to seamlessly set up your machine for Deep Learning with python. Although this […] ...

Deep Learning involving text can be fascinating to deal with. But there are two main problems to look after. First, deep learning models do not take text data directly as input. Secondly, text can be really messy to deal with when designing deep learning models. But, Keras can help with the preprocessing of text data. […] ...