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awesome-for-beginners

A list of awesome beginners-friendly projects.

big-data-analysis-using-mapreduce-in-hadoop

We explore data by using Big Data Analysis and Visualization skills. To obtain this, we perform 3 main operations. i.e. i)Data Aggregation through different sources. ii) Big Data Analysis using MapReduce and iii) Visualization through Tableau. Data Analysis is very critical in understanding the data, and what we can do with the data. For small datasets it is easier to process and obtain the results. But as for big companies, it becomes crucial for them to obtain the trends of the company for any changes need to be made. Hence we introduce Big Data Analysis to solve this problem. In this lab, we collect close to 20000 tweets, 500 articles on New York Times and 500 articles on Common Crawl Data about Entertainment, which is our main topic of discussion. Using this data, we perform preprocessing and feed it to a MapReduce to find the Word Count and Word Co-Occurrence. Using this, we find the trend of the data collected in this topic. We have used Python to perform Data Analysis.Data Analysis is very critical in understanding the data, and what we can do with the data. For small datasets it is easier to process and obtain the results. But as for big companies, it becomes crucial for them to obtain the trends of the company for any changes need to be made. Hence we introduce Big Data Analysis to solve this problem. In this lab, we collect close to 20000 tweets, 500 articles on New York Times and 500 articles on Common Crawl Data about Entertainment, which is our main topic of discussion. Using this data, we perform preprocessing and feed it to a MapReduce to find the Word Count and Word Co-Occurrence. Using this, we find the trend of the data collected in this topic. We have used Python to perform Data Analysis.

color-quantization

Coloring an image with 'K' Colors using K-Means Coloring

data-collection-and-exploratory-data-analysis

digital-resume-screening

epipolar-geometry

This project is a simple project in Computer Vision to stitch two images to form a panorama using SIFT

explainable-ai

We analyze the handwritten AND image dataset from various writers using Variational Autoencoders, Siamese Network and then pass it through a Multi-Task Learning process to get the 15 features of the images directly. This is then used to compare the handwriting of the writers

google-interview-university

A complete daily plan for studying to become a Google software engineer.

group-messenger-in-android

This is a simple Group Messenger built on Android which handles failures on one or more emulators

gym

A toolkit for developing and comparing reinforcement learning algorithms.

hough-transform

image-segmentation

k-means-from-scratch

Here we implement K-Means from scratch in Python

opencv

Open Source Computer Vision Library

panoramic-image-using-sift

pattern-recognition

probabilistic-graphical-models-on-handwritings

We compare the handwriting images of different writers from the AND dataset using Bayesian Networks using the features provided and compare the various handwritings.

rapid-pool-a-better-way-to-share-rides

Uber rides have become a convenient means of transport but irrespective of the increased demand at certain locations and time periods, there are issues such as unavailability of rides, or longer waiting periods for the customer. To resolve this issue, we provide a Data Analytics solution using Apache Spark on live streamed data to locate users heading to the same vicinity and suggest the customer to pool their rides. We use Spark as we are streaming live data and analyzing which locations are likely to face shortage of rides. This will reduce the waiting time and solve the issue of unavailability as well as provide incentives, such as reduced ride costs.

simple-distributed-hash-table

simple-dynamo

Implemented a simpler version of Amazon Dynamo through an Android App, which can recovery messages lost whenever there is a failure.

smart-shopper

A web application to track user’s items on cart, details and amount along with their previous transactions. A Walk-in Walk-out supermarket with personalized advertisements based on user’s purchases. Automated billing/checkout when leaving the store by deducting amount payable through an online wallet. Frequent items bought together are analyzed by Apriori Algorithm to find products of interest to users. RFID Readers, with specific range, are integrated to shopping carts to detect items placed and removed from the cart.

stackgan-text-to-photo-realistic-image-synthesis