an end-to-end deep learning case study Introduction The Geoscience and Remote Sensing Society — one of the well-known communities to learn and contribute to Geospatial Science has sponsored the DeepGlobe machine vision challenge in 2018, which includes the deep analysis of satellite images of Earth. The 3 challenges are - Road…

an end-to-end machine learning case study San Francisco — City San Francisco is the cultural, commercial, and financial capital of the state of California in the United States. It is the 17th most populated city in the United States and a renowned tourist destination noted for its cool summers, the Golden Gate Bridge, and…

animations with Python and Plotly Introduction An earthquake is the result of a sudden release of stored energy in the Earth’s crust that creates seismic waves. According to USGS, an earthquake is what happens when two blocks of the earth suddenly slip past one another. The surface where the two blocks…

Some interesting location-based services Introduction In this article, we will try to explore an API provided by Foursquare (a company that is well known for its location-based services). With this API, we can power location-based experiences in our app or website. Given a certain location, we can find different types of…

South Africa Crime Data Visualization — Introduction SAPS (South African Police Service) has provided crime data via Kaggle which contains the history of crime statistics from 2004 to 2015 per province and station in South Africa. The dataset contains a set of shapefiles and CSV files. Data Source → kaggle.com/slwessels/crime-statistics-for-s.. Let’s see if we can generate an…

Some interesting services that an open route provides — Introduction I have been working with geospatial data for quite a while. I always wanted to create something similar to google maps (at least a few services that it provides like geocoding, route-directions, etc). Google maps’ do provide an API for various services. But the API is not free. If you…

What the logistic regression algorithm is and how it is used in regression tasks. Introduction Logistic regression is a statistical model which is extensively used in binary classification tasks. The name logistic because it uses a logistic function to do the classification. The logistic function is also known as cross-entropy. …

What the linear regression algorithm is and how it is used in regression tasks. Introduction Regression analysis is a process of predicting a response variable given an explanatory variable. The response variable is also called a dependent variable and an explanatory variable is known as an independent variable. Given a problem…

What the KNN algorithm is and how it is used in classification tasks. Introduction KNN algorithm is a supervised classification algorithm that is mainly used to predict which category a query point belongs to, given a bunch of data values with respect to its corresponding categories (class labels). Talking from the…