Embedded systems engineer with background in machine learning, husband, father and technology enthusiast.
In this post, we presented the LSTM subclass and used it to construct a weather forecasting model. We proved its effectiveness as a subgroup of RNNs designed to detect patterns in data sequences, including numerical time series data.
In this article, we'll go over how to set up NLTK in a paperspace gradient and utilize it to carry out a variety of NLP operations during the text processing stage. Then, we will create a Keras model with the help of some NLTK tools for sentiment analysis text classification.
In this article, we demonstrate how to implement a version of a reinforcement learning technique Deep Q-Learning to create an AI agent capable of playing Checkers at a decent level.
In this blog post we explore the differences between deed-forward and feedback neural networks, look at CNNs and RNNs, examine popular examples of Neural Network architectures, and their use cases.
In this article, we examine the effects of batch size on DL model training times and accuracies, and go on to describe a methodology for finding the maximum batch size for any given task.
In this tutorial, we start by introducing techniques for extracting audio features from music data. We then show how to implement a music genre classifier from scratch in TensorFlow/Keras using those features calculated by the Librosa library.
In our latest blogpost, we shine a spotlight on the Nvidia A100 to take a technical examination of the technology behind them, their components, architecture, and how the innovations within have made them the best tool for deep learning.
In this article, we ask what GPU memory bandwidth is, and examine why it should be taken into consideration as one of the qualities an ML/DL expert should look for in a machine learning platform.
