Here is how looking into the data will tell you that CFVs are not sporadic!
When a ceasefire violation (CFV) happens along the Line of Control (LoC) and international border, such occurrences are considered merely sporadic and against the grain of a written agreement between the two countries. In our study, we aim to rectify the knowledge-gap with predictions on the number of CFVs along the India-Pakistan LoC, using python to identify the best model (SARIMA vs Prophet) and data visualisation tools like Tableau to recognise susceptible sectors. Our study could be useful for Indian military experts to be better prepared beforehand against impending CFVs. …
Identify faces and extract up to 6 facial features with few lines of code!
Detection of facial landmarks and their feature points plays an important role in many facial image-related applications such as face recognition or verification, facial expression analysis, pose normalization, and 3D face reconstruction.
Detection of facial features is easy for persons; however, for machines it is not an easy task at all. The difficulty comes from high inter-personal variation (e.g., gender, race), intra-personal changes (e.g., pose, expression), and from acquisition conditions (e.g., lighting, image resolution). As a beginner in computer vision, I am sure all of us would have faced a similar challenge of detecting features. …
Witness the power of deep learning on huge datasets!
In this part 2 of the article, we will make our neural network (ANN) using keras framework.
For Part 1 (using traditional classifier), kindly visit the following link:
For source code, visit the following link:
We will use the data processed in Part 1. The processed dataset consists of 20 selected features and we need to classify whether the asteroid is potentially hazardous or not. The target variable is divided into 2 classes.
Keras is a simple tool for constructing a neural network. …
Witness the power of deep learning on huge datasets!
Asteroids are small, rocky objects that orbit the Sun. Although they orbit the Sun just like the planets, they are much smaller than them. Potentially Hazardous Asteroid(PHA) is a near-Earth object — either an asteroid or a comet — with an orbit that can make close approaches to the Earth and large enough to cause significant regional damage in the event of impact.
I will explain how to detect potentially hazardous asteroids initially using traditional machine learning classifiers and later using artificial neural network to draw a comparison between both. …
Explore the power of Yellowbrick and mlxtend!
Pulsars are highly magnetized rotating neutron stars that emit beams of electromagnetic radiation out of their magnetic poles. Pulsars are one of the candidates for the source of ultra-high-energy cosmic rays. They are important as they help study extreme states of matter, search for exoplanets, measure cosmic distances and find gravitational waves.
We will do a classification on pulsars covering all the aspects of the problem including EDA using automated EDA module, feature selection using feature importance, hyperparameter tuning using RandomizedSearchCV, dealing with imbalanced classes and visualizations using Yellowbrick and mlxtend.
For the source code please visit the following…
Delhi Metro Rail Corporation (DMRC) is the fifth largest metro network in the world. Kashmere Gate Station on the Yellow Line is the busiest intersections among all. We have focused on designing a model (using Python) of the ridership pattern employing material balance phenomenon. This includes information on how the ridership varied during the day (peak and lean hours), de-boarding weightage of the station and passenger accumulation at the station.
The model could be of great use to the Metro Corporation for optimizing the train frequency during different hours of the day, providing hassle-free commute by controlling the passenger flow.
The system under consideration for our model was the junction of Kashmere Gate (KG), New Delhi, India. …
Exploratory Data Analysis made simple in few lines of code!
Exploratory Data Analysis refers to the critical process of performing initial investigations on data so as to discover patterns,to spot anomalies,to test hypothesis and to check assumptions with the help of summary statistics and graphical representations.
However, EDA generally takes a lot of time and effort in the ML workflow and as we all know time is money! As a beginner in data science, I am sure all of us would have faced a similar challenge of comprehensively doing EDA. To cover variety of visualizations while exploring the data, it needs endless lines of codes. …
Build beautiful and interactive web apps with zero web development experience!
For data analysts, visualization and presentation of their hard worked ML projects are at least as important as the analysis part of their projects. For long, there has been a feeling of deficiency among the analysts with respect to this but not anymore!
Streamlit is an open-source Python library that makes it easy to build beautiful custom web-apps for machine learning and data science. It lets your app update live as you edit and save your file. All you need is your favorite editor (I prefer Spyder which is included with Anaconda. Visit https://www.spyder-ide.org/ …