We apply our coding skills to a wide range of datasets to solve real-world problems. Here are some inspirational ideas and their implementations from our brilliant community members. Check out these projects below!
Face Detection Using Python
This is a simple program to detect faces in an image using Cascade classifier in skimage feature module. It uses a trained file that can detect frontal faces. The detector model is instantiated with this trained file and takes the image as input along with parameters for the minimum and maximum rectangular sized to scan for, the scaling factor for the scanner, and a step ratio. The detected faces are returned as circles with the coordinates of the top left corner, length and width.
Shreyas Anand
Online BOT Bidding Exploratory Data Analysis
Exploratory Data Analysis on an online bidding dataset using Python libraries, Pandas, NumPy, Matplotlib, Seaborn, by plotting bidding behaviors over time indicating behavioral difference between human bidders and robot bidders.
Shreyas Anand
Wikipedia Page Comparison
Wikipedia is a Python library that makes it easy to access and parse data from two Wikipedia pages and compares them. This program is created using the wikipedia module. The program takes two inputs from the user, for the names of the pages to be compared. Then python extracts data from the wikipedia page and runs a similarity check to display the similarity as percentage. The program also prints the images available on the wikipedia page.
Shreyas Anand
IPL Score Predictor
What if I say we can make an app that can predict the outcome of IPL matches, Yeah! with the power of Machines and Deep Learning, you can do these types of amazing stuff and this project is all about it.
In particular, here we will be looking at how you can train a model from scratch and embed it in the web app using simple and powerful libraries like sklearn, pandas, and flask. Also, some web development is involved.