Deep Learning

Multiclass bearing fault classification using features learned by a deep neural network

Accurate classification of fault is important for condition based maintenance (CBM) applications. Two main approaches commonly used for …

Biswajit Sahoo, A. R. Mohanty

IndexedSlices in Tensorflow

Run in Google Colab View source on GitHub Download notebook In this post, we will discuss about IndexedSlices class of Tensorflow. We will try to answer the following questions in this blog:

Apr 1, 2021 5 min read Blog, Tensorflow, Deep Learning, Attention Mechanism

Tensorflow 2 code for Attention Mechanisms chapter of Dive into Deep Learning (D2L) book

View source on GitHub Download code (.zip) This code has been merged with D2L book. See PR: 1756, 1768 This post contains Tensorflow 2 code for Attention Mechanisms chapter of Dive into Deep Learning (D2L) book.

Mar 10, 2021 1 min read Blog, Tensorflow, Attention Mechanism, Transformer

Reading multiple files in Tensorflow 2 using Sequence

Run in Google Colab View source on GitHub Download notebook In this post, we will read multiple csv files using Tensroflow Sequence. In an earlier post we had demonstrated the procedure for reading multiple csv files using a custom generator.

Dec 26, 2020 17 min read Blog, Tensorflow, Machine Learning, Deep Learning

Reading multiple csv files in PyTorch

Run in Google Colab View source on GitHub Download notebook In many engineering applications data are usually stored in CSV (Comma Separated Values) files. In big data applications, it’s not uncommon to obtain thousands of csv files.

Dec 19, 2020 18 min read Blog, PyTorch, Machine Learning, Deep Learning

Data-Driven Remaining Useful Life (RUL) Prediction

Aim of this project is to produce reproducible results in condition monitoring. We will apply some of the standard machine learning techniques to publicly available datasets and show the results with code for remaining useful life (RUL) prediction task. This is an ongoing project and will evolve over time. Related notebooks can be found at this github page.

Efficiently reading multiple files in Tensorflow 2

Note: Whether this method is efficient or not is contestable. Efficiency of a data input pipeline depends on many factors. How efficiently data are loaded? What is the computer architecture on which computations are being done?

May 17, 2020 18 min read Blog, Tensorflow, Deep Learning

Reading multiple files in Tensorflow 2

Run in Google Colab View source on GitHub Download notebook In this post, we will read multiple .csv files into Tensorflow using generators. But the method we will discuss is general enough to work for other file formats as well.

Jan 9, 2020 20 min read Blog, Machine Learning, Deep Learning, Tensorflow

Using Python Generators

Run in Google Colab View source on GitHub Download notebook In this post, we will discuss about generators in python. In this age of big data it is not unlikely to encounter a large dataset that can’t be loaded into RAM.

Jun 29, 2019 8 min read Blog, Python, Deep Learning, Tensorflow

Data-Driven Machinery Fault Diagnosis

Aim of this project is to produce reproducible results in condition monitoring. We will apply some of the standard machine learning techniques to publicly available machinery datasets and show the results with code for fault diagnosis task. This is an ongoing project and will evolve over time. Related notebooks and data can be found at this github page.