jailukanna's Projects
Sentimental analysis of movie reviews
100+ python programming exercise problem discussed ,explained and solved in different ways
100days of Python coding
Let's build something productive in less than 100 Lines of Code.
For this project we will use the “The 20 Newsgroups” data set available at: http://qwone.com/~jason/20Newsgroups/ To simplify your project you are allowed to use the version of the “20 Newsgroups” data set that comes preloaded with scikit-learn library. To load is you can use the following code: You can learn more from the scikit-learn documentation at: https://scikit- learn.org/0.19/modules/generated/sklearn.datasets.fetch_20newsgroups.html#sklearn.datasets.fetch_ 20newsgroups Project Description The goal of the project is to train different classifier and test the outcomes trying to achieve as high accuracy as you can. Please make sure you are clear on which metrics you are using to measure how good is your classification. You can use as many techniques as you have learned in class. Especially may be helpful preparing and transforming the data. Selecting the appropriate classification algorithm with the optimal parameters will give you different results. Final deliverables: You can work as a group but must submit each individually the following project deliverable: 1. Project report (Word or PDF) that describes in detail your project activities, what specific steps you did, what challenges you encountered and how you resolved them. a. Describe the different models you ran and the different results that you achieved with each model b. Describe the different types of data preparation and transformation you performed and how the different data steps affected the outcomes #Loading the 20 Newsgroup data set. Example loading the training data. from sklearn.datasets import fetch_20newsgroups mydata_train = fetch_20newsgroups(subset='train', shuffle=True) c. Finally describe your best model and outcome, show the results you achieve and comment on your insights and learnings from the project 2. Jupyter Notebook in Python 3.6 or higher that can be executed without errors a. The code must be very well documented explaining and self-explanatory from the notebook b. The code must run without errors c. The code must contain at least three (3) different models – trained and tested – showing the results d. Any interesting data transformations must be highlighted and their impact on the outcome must be described and explained 3. Configuration and setup file with user instruction a. The file must briefly describe how I should set up and execute your notebook. The easier it is for me to run and evaluate your code, but better your project will be accepted
Data cleaning a raw dataset. Analyze the data and apply data visualization techniques to support insights.
Extract text information from Aadhaar Card using tesseract-ocr :sunglasses:
An accident avoidance program that raises alert when nearby vehicles are moving at a relative speed faster than a threshold value, additionally it logs some data onto NEM-Mijin blockchain network
Using deep learning and computer vision(pytorch) to detect accidents on dashcam and report it to nearby emergency services with valid accident images
Automatic incident detection on Indian Roads using Artificial Intelligence. Model is trained using Tensorflow object detection API. Use of model after training in Python script as well as in Android application is also demonstrated in this project.
This Is a Pre-trained Model for Detecting Accidents
This project will help you to detect accident using raspberry pi
Event Processing Networks for Traffic Congestion Management for Accident Prediction, Notification & Assistance.
This Project involves detection or sending of alarm before car accident.
In India, there are a lot of accidents taking place every day due to mishaps. As the population grows the no. of cars and accidents is directly proportional. This example program shows how to find frontal human faces in an image and estimate their pose. The pose takes the form of 68 landmarks. These are points on the face such as the corners of the mouth, along the eyebrows, on the eyes, and so forth.
Code Repository for Advanced REST APIs with Flask and Python, Published by Packt
The Zipru scraper developed in the Advanced Web Scraping Tutorial.
I am a full-stack engineer for AI projects, glad to share my experience. pratices make the top engineer.
iNeuron Project - AirBnB Data Analysis, automated EDA & reports, Visualizations with WordClouds on textual data.
This repository contains three ways to obtain arbitrage which are Dual Listing, Options and Statistical Arbitrage. These are projects in collaboration with Optiver and have been peer-reviewed by staff members of Optiver.
fetching json data from database and inserting values into mysql database with python using flask
Detecting apples in images
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent