Shubham Darak's repositories
Lane-Detection-and-Departure-Warning-System
System will detect Lane and will warn if car is moving out of the lane.
Fake-News-Classifier
Implemented the fake news classifier using Django as a server-side framework and Html, CSS, Bootstrap as a frontend technology. The Deep Learning model included an Embedding layer and Long Short-Term Memory layers which provide complete sentiment of the sentence. The system accepts text news as an input and predicts the probability of news being True or fake.
Data-Structures-and-Algorithms
The Repository is comprised of competitive coding questions solved using C++ language
Lane_Departure_warning_system-using-CNN
lane is detected and warning is generated when user departs from Lane
Moneymize
Money management application
Statistical-Crowd-Counting
Implemented the project using PostgreSQL as a database, Django as a server-side framework, and Html, CSS, bootstrap as a frontend technology. The Deep Learning model was used to predict crowd count from video frames. The project provides area wise statistical analysis of crowd flow throughout the shops, malls, etc.
Malaria-Detection-system
System is composed of Deep Residual network used to classify the cells as Infected or Uninfected.
ShubhamDarak37.github.io
Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes
ThinkStats2
Text and supporting code for Think Stats, 2nd Edition
Traffic-Sign-Recognition-System
system comprises of three sets of CONV -> RELU -> BN -> POOL layers and 2 fully connected layers, system gained validation accuracy of 95%. System recognizes 43 different classes of traffic signs.