ayu1729

active_learning_trial

attendance_project

awesome-deep-learning

A list of resources one can find useful to get started with ML (specifically Deep Learning) or to learn a particular topic.

ayu1729

Bosch-Production-Line-Performance

BTC_Sentiment

Presentation Link: https://youtu.be/EyskhUmbIXg

coursera-deep-learning-specialization

Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning.ai: (i) Neural Networks and Deep Learning; (ii) Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization; (iii) Structuring Machine Learning Projects; (iv) Convolutional Neural Networks; (v) Sequence Models

DBAL

Implementation of Deep Bayesian Active Learning with Image Data with modAL (python module for Active Learning)

deep-active-learning

Deep Active Learning

Deep-Bayesian-Active-Learning

Code for Deep Bayesian Active Learning (ICML 2017)

ayu1729/active_learning_trial

ayu1729/attendance_project

ayu1729/awesome-deep-learning

A list of resources one can find useful to get started with ML (specifically Deep Learning) or to learn a particular topic.

ayu1729/ayu1729

ayu1729/Bosch-Production-Line-Performance

ayu1729/BTC_Sentiment

Presentation Link: https://youtu.be/EyskhUmbIXg

ayu1729/coursera-deep-learning-specialization

Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning.ai: (i) Neural Networks and Deep Learning; (ii) Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization; (iii) Structuring Machine Learning Projects; (iv) Convolutional Neural Networks; (v) Sequence Models

ayu1729/DBAL

Implementation of Deep Bayesian Active Learning with Image Data with modAL (python module for Active Learning)

ayu1729/deep-active-learning

Deep Active Learning

ayu1729/Deep-Bayesian-Active-Learning

Code for Deep Bayesian Active Learning (ICML 2017)

ayu1729/Domain-Specific-Question-Answering-DevRev

Domain adaptation in open domain question answering is tackled through theme specific rankers. We also propose a novel resource allocation algorithm to select the number of paragraph to be examined for extracting the answering. Finished 1st among participating IITs in Inter IIT tech Meet 11.0

ayu1729/Fake_News_Classifier

ayu1729/FDIR_Neural_Networks

The goal of this project is to develop a failure detection, isolation and recovery algorithm (FDIR) for a cubesat, but using machine learning and neural networks instead of the more traditional methods.

ayu1729/Get-Started-NWoC20

Instructions on how to get started with NWoC :)

ayu1729/Hindi_language_modelling

ayu1729/hog-svm-inria

Pedestrian classification from photos using the Linear SVM and HOG features in INRIA dataset

ayu1729/indoor_localistion

For applying deep learning models on RSS values for indoor localisation in IOT.

ayu1729/LAM_Demo

Demo package for colab tutorial

ayu1729/Localization_via_WiFi_Fingerprinting

Multi-Floor Indoor Localization based on Wi-Fi Fingerprinting using various Machine Learning models on the UJIIndoorLoc dataset.

ayu1729/Pedestrian-Detection

Pedestrian Detection using Fast-R-CNN with Pytorch.

ayu1729/PersonDetection

Person Detection using HOG Feature and SVM Classifier

ayu1729/prompt-to-prompt

ayu1729/sound_event_detection

ayu1729/submodlib

Summarize Massive Datasets using Submodular Optimization

ayu1729/THE_CHANDRAYAAN_MOON_MAPPING_CHALLENGE

copy of INTER IIT ISRO project

ayu1729/virufy-data