Beginning this year, I had been taking interviews for a job change in Data Science (DS)/Machine Learning (ML)/Deep Learning (DL) field in India. In the process of 30-40 days of job hunt, I took interviews […]
As in my previous post “Setting up Deep Learning in Windows : Installing Keras with Tensorflow-GPU”, I ran cifar-10.py, an object recognition task using shallow 3-layered convolution neural network (CNN) on CIFAR-10 image dataset. We achieved […]
There is a lot of hoopla surrounding Deep Learning along with the ignorance about how to actually start getting hands dirty in deep learning. This problem would be more pervasive among the beginners and developers […]
Text classification is a problem where we have fixed set of classes/categories and any given text is assigned to one of these categories. In contrast, Text clustering is the task of grouping a set of unlabeled texts in […]
I participated in one HackerEarth Challenge, “Predict the Happiness” and hence I am coming up with this tutorial of the solution submitted by me which gives 88% accuracy on the test data. I was ranked […]
Automatic change detection in images of a region acquired at different times is one the most interesting topics of image processing. Such images are known as multi temporal images. Change detection involves the analysis of […]
Similar to our previous post “Voice Gender Detection“, this blog-post focuses on a beginner’s method to answer the question ‘who is the speaker‘ in the speech file. Recently, lot of voice biometric systems have been […]
This blog-post is third in the series of blog-posts covering applications of “Topic Modelling” from simple Wikipedia articles. Before reading this post, I would suggest reading our earlier two articles here and here. In the […]
This blog-post is second in the series of blog-posts covering “Topic Modelling” from simple Wikipedia articles. Before reading this post, I would suggest reading our first article here. In the first step towards Topic modeling […]
A huge number of text articles are generated everyday from different publishing houses, blogs, media, etc. This leads to one of the major tasks in natural language processing i.e. effectively managing, searching and categorizing articles […]
Keystroke dynamics is the study of the typing patterns of people to distinguish them from one another, based on of these patterns. Every user has a certain way of typing that separates him from other […]
There is a lot of information that can be extracted from a speech sample, for example, who is the speaker, what is the gender of the speaker, what is the language being spoken, with what […]
The Naive Bayes classifier is a frequently encountered term in the blog posts here; it has been used in the previous articles for building an email spam filter and for performing sentiment analysis on movie reviews. Thus […]
A bi-gram model based language identification from text or tweets.
This is a description of mathematical formulation for understanding SVM classification.
K-means clustering illustration
tutorial on sentiment analysis on movie reviews using machine learning techniques. It describes famous tf-idf text features for text classification task.
shows python based tutorial on text classification of emails into spam and non-spam categories. It uses bag of word features and machine learning models.