Pinned Repositories
async-http-requests-tut
Making multiple HTTP requests using Python (synchronous, multiprocessing, multithreading, asyncio)
Boston-House-Prediction
Used a dataset of house prices with some features including Zen, chas and no of bedrooms, etc to create a model that predicts the price of a new house,It uses the concept.
Breast-Cancer-Detection
This projects or the machine learning model detects breast cancer It helps in getting the count of the malignant and benign cells.We are going to visualize the plot using seaborne library and we split the data into 75 percent training and 25 percent training data set and we use the linear regression model, svm,decision tree and random forest classifier to predict the correct accuracy of the disease
Chat-app-using-flask-socketIO-and-MongoDB
Concurrent-Programming-in-Python
Python, Async, Concurrency, Asyncio, await
Image-download-using-Threading-and-Multiprocessing
ML-prob-using-Threading
Multiprocessing-Parellel-Programming-in-Python
Multithreading-Python-Parellel-Programming
Network-Congestion-model
In the context of telecommunications industry, one of the most important issues that industry faces is network congestion. It has been shown that congestion, even if for smaller durations, has a negative impact on customer loyalty, especially in price sensitive markets. To solve this problem effectively, it becomes imperative for firms to be able to predict congestion in advance and take proactive actions
Shreya3515's Repositories
Shreya3515/async-http-requests-tut
Making multiple HTTP requests using Python (synchronous, multiprocessing, multithreading, asyncio)
Shreya3515/Boston-House-Prediction
Used a dataset of house prices with some features including Zen, chas and no of bedrooms, etc to create a model that predicts the price of a new house,It uses the concept.
Shreya3515/Breast-Cancer-Detection
This projects or the machine learning model detects breast cancer It helps in getting the count of the malignant and benign cells.We are going to visualize the plot using seaborne library and we split the data into 75 percent training and 25 percent training data set and we use the linear regression model, svm,decision tree and random forest classifier to predict the correct accuracy of the disease
Shreya3515/Chat-app-using-flask-socketIO-and-MongoDB
Shreya3515/Concurrent-Programming-in-Python
Python, Async, Concurrency, Asyncio, await
Shreya3515/Image-download-using-Threading-and-Multiprocessing
Shreya3515/ML-prob-using-Threading
Shreya3515/Multiprocessing-Parellel-Programming-in-Python
Shreya3515/Multithreading-Python-Parellel-Programming
Shreya3515/Network-Congestion-model
In the context of telecommunications industry, one of the most important issues that industry faces is network congestion. It has been shown that congestion, even if for smaller durations, has a negative impact on customer loyalty, especially in price sensitive markets. To solve this problem effectively, it becomes imperative for firms to be able to predict congestion in advance and take proactive actions
Shreya3515/EDA_on_Lending_Club_Dataset
EDA on Lending Club Dataset
Shreya3515/Making-multiple-HTTP-requests-using-Python
Making multiple HTTP requests using Python (synchronous, multiprocessing, multithreading, asyncio)