Pinned Repositories
DO180-apps
DO180 Repository for Sample Applications
Indian-Cities-JSON
a json file containing 1220 indian cities and their respective states
ishita65.github.io
JPMC-tech-task-1-PY3
K-means-Image-Compression-with-Interactive-Controls
Compression of High Definition images by applying K-Means Clustering on pixels. K-Means Clustering is a sort of unsupervised Machine Learning algorithm. It can be used to separate unlabelled data like image colors into distinct groups. We used K-Means Clustering to perform image compression. We grouped pixels in an image by their similarity in color in order to reduce the total number of colors within that image.
LeetCode-Solutions
A compilation of all the Leetcode solutions.
ProblemSets
Sentiment-Tracker
Analysis of sentiment by building a logistic regression model to classify movie reviews as either positive or negative. Tokenisation and stemming of words by removing less useful data such as html tags, punctuation and emojis. Term Frequency-Inverse Document Frequency is used to down-weight data that that occur across multiple documents from both classes.
test_demo
ishita65's Repositories
ishita65/DO180-apps
DO180 Repository for Sample Applications
ishita65/Indian-Cities-JSON
a json file containing 1220 indian cities and their respective states
ishita65/ishita65.github.io
ishita65/JPMC-tech-task-1-PY3
ishita65/K-means-Image-Compression-with-Interactive-Controls
Compression of High Definition images by applying K-Means Clustering on pixels. K-Means Clustering is a sort of unsupervised Machine Learning algorithm. It can be used to separate unlabelled data like image colors into distinct groups. We used K-Means Clustering to perform image compression. We grouped pixels in an image by their similarity in color in order to reduce the total number of colors within that image.
ishita65/LeetCode-Solutions
A compilation of all the Leetcode solutions.
ishita65/ProblemSets
ishita65/Sentiment-Tracker
Analysis of sentiment by building a logistic regression model to classify movie reviews as either positive or negative. Tokenisation and stemming of words by removing less useful data such as html tags, punctuation and emojis. Term Frequency-Inverse Document Frequency is used to down-weight data that that occur across multiple documents from both classes.
ishita65/test_demo
ishita65/Vita
Bringing life back to your college life.