Pinned Repositories
akankshadara.github.io
A lightweight, customizable single-page personal portfolio website template built with JavaScript and Sass
ark-tweet-nlp-python
Simple Python wrapper around runTagger.sh of ark-tweet-nlp
Audio-analysis-for-weighting-words-of-a-speech
Assignment under the course Information Retrieval
Davies_Bouldin_Index_KMeans
This repository contains a naive implementation of Davies Bouldin Index used to find the optimum number of clusters in K-Means clustering.
Diabetes_Prediction_deep_learning
This repository contains code used for prediction of diabetes on the Pima Indiana Diabetes dataset using neural networks.
Drishti_ocr_tesseract
Drishti is a software that converts printed Hindi text to Braille. Tesseract Open source library is used as an OCR to scan and convert printed Hindi text to unicode characters. These characters are encoded into binary strings which are used to represent alphabets in braille. Arduino is used to display the characters by blinking of corresponsing LED's. For the functioning of this software, You should have installed Tesseract and Leptonica and trained it for Hindi. You can download the dependencies using this Shell script: [Dependencies.sh](https://github.com/rahulchhabra07/Drishti/blob/master/Dependencies.sh). After training, feed a JPEG image file containg printed Hindi text to the Python file. This creates a dialog box showing, the original image and translated text. Now click on next for displaying the text using arduino board.
Geotagging_Images
A python script to extract the exif data from an image file. The latitude and longitude information from this exif data is used to specify the street address of the image.
TCP-IP-Packet-Sniffer
A packet sniffer allows the user to view and capture all the information that is transmitted over the network, as packets of data [I]. The aim of this application is to read packets that travel across various layers of the Transmission Control Protocol/Internet Protocol (TCP/IP) model of network architecture. The packet sniffer, or the network traffic monitoring framework will analyze the network traffic so as to allow users to get a practical understanding of the flow of packets in a network. It will help them gain some insights on the header structures of different protocols, differences between the protocols at different network layers, similarities between the protocols on the same network layer and change in size of the payload as the packet travels through the network stack. It will be used to capture and analyze the following protocols’ header information from the packets: The packets captured will be analyzed to extract and display the header information along with other relevant parameters for the selected protocols.
Text-Summarization
A python class to generate a summary for an audio speech on the basis of term frequencies and keywords that were stressed upon in the audio file.
Yazaki_file_manager
A GUI-based software “Applicator Drawing Control Management” which maintains the logs and database of the part drawings and ensures secure access to these files.
akankshadara's Repositories
akankshadara/Davies_Bouldin_Index_KMeans
This repository contains a naive implementation of Davies Bouldin Index used to find the optimum number of clusters in K-Means clustering.
akankshadara/TCP-IP-Packet-Sniffer
A packet sniffer allows the user to view and capture all the information that is transmitted over the network, as packets of data [I]. The aim of this application is to read packets that travel across various layers of the Transmission Control Protocol/Internet Protocol (TCP/IP) model of network architecture. The packet sniffer, or the network traffic monitoring framework will analyze the network traffic so as to allow users to get a practical understanding of the flow of packets in a network. It will help them gain some insights on the header structures of different protocols, differences between the protocols at different network layers, similarities between the protocols on the same network layer and change in size of the payload as the packet travels through the network stack. It will be used to capture and analyze the following protocols’ header information from the packets: The packets captured will be analyzed to extract and display the header information along with other relevant parameters for the selected protocols.
akankshadara/Geotagging_Images
A python script to extract the exif data from an image file. The latitude and longitude information from this exif data is used to specify the street address of the image.
akankshadara/Diabetes_Prediction_deep_learning
This repository contains code used for prediction of diabetes on the Pima Indiana Diabetes dataset using neural networks.
akankshadara/Text-Summarization
A python class to generate a summary for an audio speech on the basis of term frequencies and keywords that were stressed upon in the audio file.
akankshadara/akankshadara.github.io
A lightweight, customizable single-page personal portfolio website template built with JavaScript and Sass
akankshadara/ark-tweet-nlp-python
Simple Python wrapper around runTagger.sh of ark-tweet-nlp
akankshadara/Audio-analysis-for-weighting-words-of-a-speech
Assignment under the course Information Retrieval
akankshadara/awesome-deep-learning-papers
The most cited deep learning papers
akankshadara/Competetive-programming
akankshadara/Cricket-Analytics-using-OpenCV-and-Machine-Learning
The project was to retrain the Haar Classifier in the Viola Jones algorithm to identify players on the field and track their positions.
akankshadara/Data_Mining_Lab
Python Data Mining
akankshadara/DataQuest_practice-codes
Data Science using numpy,pandas, matplotlib, sklearn
akankshadara/deeplearning4nlp-tutorial
Hands-on tutorial on deep learning with a special focus on Natural Language Processing (NLP)
akankshadara/ERPLAG-Compiler
akankshadara/functional_programming_scheme
Contains codes for small functions implemented using Scheme
akankshadara/HMV-Ensemble-for-disease-prediction
akankshadara/IR-implementation
Implementation of basic Information Retrieval systems in Python
akankshadara/MicroProcessors_Fire_Alarm_System
This system checks for abnormal smoke content in a room every two seconds. Under abnormal conditions it throws open two doors and two windows and opens a valve that releases the gas to put-out the fire. An Alarm is also sounded; this alarm is sounded until the smoke level in the room drops to an acceptable level. The smoke detection system is made up of two smoke sensors placed on the ceiling of the room. When the smoke level comes back below the danger level, the doors, windows and valves are closed.
akankshadara/MIPS-Verilog
Datapath implementation of MIPS architecture in Verilog Tested on : ModelSIM
akankshadara/mM_task
akankshadara/NLP-progress
Repository to track the progress in Natural Language Processing (NLP), including the datasets and the current state-of-the-art for the most common NLP tasks.
akankshadara/opencv
Open Source Computer Vision Library
akankshadara/Practical_NLP_in_PyTorch
A repository containing tutorials for practical NLP using PyTorch
akankshadara/recruiting-exercises
Deliverr coding exercises for engineering
akankshadara/Sarcasm_Detection_Twitter
Sarcasm detection is a particularly difficult task even for humans. This repository contains the implementation of a research paper by Ashwin Rajadesingan in python ML libraries.
akankshadara/scikit-learn
scikit-learn: machine learning in Python
akankshadara/spell_checker
The spell checker works by: reading in and tokenizing a vocabulary of correctly spelled words, reading in, cleaning, and tokenizing the piece of text we want spell checked, comparing each word (token) in the piece of text with each word in the vocabulary and returning the ones that weren't found (incorrectly spelled words). The file dictionary.txt contains a sequence of correctly spelled words, which we'll use to seed our vocabulary. The file story.txt is a piece of text containing some misspelled words. In the following code cell, we added the spell checker we wrote so far from the previous mission.
akankshadara/system-design-primer
Learn how to design large-scale systems. Prep for the system design interview. Includes Anki flashcards.
akankshadara/textrank
TextRank implementation in Python.