There are no reviews yet. Be the first to send feedback to the community and the maintainers!
Financial-Time-series-analysis-for-High-Frequency-Trading
Financial time-series forecasting has long been a challenging problem because of the inherently noisy and stochastic nature of the market. In the field of High-Frequency Trading (HFT), forecasting for trading purposes is even a more challenging task since an automated inference system is required to be both accurate and fast. In this project, we have implemented a shallow-architecture methodology for the forecasting of financial time-series data, which gives state-of-the-art results. This architecture has been trained and tested on the benchmark Limit Order Book(LOB) FI-2010 dataset, and the corresponding results are compared and analyzed using a variety of measures.TrashBox-testandvalid
Dataset of trash objects for waste classification and detectionSalient-object-detection-using-MST
Machine-Learning-Approach-to-Software-Requirements-Prioritization
Using Genetic Algorithm to prioritize the software requirements of a projectHCI-project
Context-based-Flagging-of-objects-in-Satellite-Imagery
Forecasting-CPU-usage-using-LSTM
Driver-Drowsiness-detection-system
Driver drowsinness detection system is implemented in python and opencv. The aim is to make a system that can reduce the road accidents by sounding alarm when a driver is feeling sleepy.TrashBox-VGG19_model
Mitigating-Unfairness-and-Bias-in-Cold-Start-Recommenders
to study bias and fairness in recommender systems have focused on improving fairness and mitigating bias only in situations and for items where a history of the user profile already exists. In this project, we explore the bias against new items without any feedback history which are added to recommender systems.e-voting-system
E-commerce-application
MERN stack web applicationEmployee-Appraisal-Management-System
Mean stack web application to perform CRUD operations on employee database and on appraisal detailsAttack-and-Anomaly-Detection-in-IoT-Sensors-and-Sites-Using-Machine-Learning-Approaches
FuzzBuzz-TDD
Project on FuzzBuzz program using a software development process called Task-Driven Development (TDD) that relies on the repetition of a very short development cycle: requirements are turned into very specific test cases, then the code is improved so that the tests pass.Handwritten-digit-classification-using-CNN
Handwritten digit classification using CNN - Build two Neural Networks capable to perform handwritten digits classification using the MNIST dataset. The first Network is a simple Multi-layer Perceptron (MLP) and the second one is a Convolutional Neural Network (CNN). when given an input our algorithm will say, with some associated error, what type of digit this input represents.Building-Damage-Detection-and-Classification-using-Deep-Learning
Love Open Source and this site? Check out how you can help us