Data Science 911 Project

Last Updated on May 3, 2021

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This is my data Science project on 911 calls from the 911 emergency calls dataset on kaggle. This project was done in Python using jupyter.

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Image Processing

Last Updated on May 3, 2021

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What is image processing ?

The aim of pre-processing is an improvement of the image data that suppresses unwilling distortions or enhances some image features important for further processing, although geometric transformations of images (e.g. rotation, scaling, translation) are classified among pre-processing methods here since similar.

Preprocessing refers to all the transformations on the raw data before it is fed to the machine learning or deep learning algorithm. For instance, training a convolutional neural network on raw images will probably lead to bad classification performances.


convolutional neural network

convolutional neural network (CNN) is a type of artificial neural network used in image recognition and processing that is specifically designed to process pixel data. ... A neural network is a system of hardware and/or software patterned after the operation of neurons in the human brain.


CNNs are used for image classification and recognition because of its high accuracy. The CNN follows a hierarchical model which works on building a network, like a funnel, and finally gives out a fully-connected layer where all the neurons are connected to each other and the output is processed.


Problem description:  Case study , We have a dataset has 3 subfolders inside it are single prediction contains only 2 images to test the model and prediction so that we know our CNN model is working , test set with 2000 images (1000 of dogs and 1000 of cats) where we will evaluate our model , training set contains 8000 images 4000 of cats and 4000 of dogs as we are going to train our CNN model on these images of dogs and cats . so basically our CNN model is going to predict whether the image given is of a a cat or a dog. By generating random number on google then choosing the image .  Eg: cat


Prediction for CAT

PREDICTION FOR DOG

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Social Distance Monitoring System(Python And Opencv)

Last Updated on May 3, 2021

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Social distancing is one of the community mitigation measures that may be recommended during Covid-19 pandemics. Social distancing can reduce virus transmission by increasing physical distance or reducing frequency of congregation in socially dense community settings, such as ATM,Airport Or market place .

Covid-19 pandemics have demonstrated that we cannot expect to contain geographically the next influenza pandemic in the location it emerges, nor can we expect to prevent international spread of infection for more than a short period. Vaccines are not expected to be available during the early stage of the next pandemic (1), a Therefore, we came up with this system to limit the spread of COVID via ensuring social distancing among people. It will use cctv camera feed to identify social distancing violations

We are first going to apply object detection using a YOLOv3 model trained on a coco dataset that has 80 classes. YOLO uses darknet frameworks to process incoming feed frame by frame. It returns the detections with their IDs, centroids, corner coordinates and the confidences in the form of multidimensional ndarrays. We receive that information and remove the IDs that are not a “person”. We will draw bounding boxes to highlight the detections in frames. Then we use centroids to calculate the euclidean distance between people in pixels. Then we will check if the distance between two centroids is less than the configured value then the system will throw an alert with a beeping sound and will turn the bounding boxes of violators to red.



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Nyc Yellow Taxi Prediction

Last Updated on May 3, 2021

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I did this project in my second semester of Mtech studies at Ahmedabad University. In NYC, taxicabs come in two varieties: yellow and green; they are widely recognizable symbols of the city. Taxis painted yellow (medallion taxis) are able to pick up passengers anywhere in the five boroughs. in Upper Manhattan, the Bronx, Brooklyn, Queens, Staten Island. The yellow taxi cab was first introduced in 1915 by a car salesman named John Hertz. Hertz decided to paint his taxis yellow because of a study by a Chicago university to establish what color would grab the attention of passers-by more easily. The results proved that yellow with a touch of red was most noticeable. As a result, Hertz started to paint all his taxicabs yellow and went on to start the Chicago-based Yellow Cab Company in 1915. During pre-processing of data there were many outliers such as there was 100 dollars fare for a 0-mile trip. Then there were few outliers in rate code id. We pre-processed and removed them all and cleaned the data. After cleaning the data we visualized data in which we got different insights people like to travel single in the taxi. Area 236 has the most taxi bookings. Also, we observed that at midnight (1 to 6 am) people don’t like to travel much often. FOr the prediction part, we predicted the fare using different regression methods and for taxi booking, we used k means clustering.

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Predicting Employees Under Stress For Pre-Emptive Remediation Using Machine Learning Algorithm

Last Updated on May 3, 2021

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With the ongoing COVID-19 pandemic, businesses and organizations have acclimated to unconventional and different working ways and patterns, like working from home, working with limited employees at office premises. With the new normal here to stay for the recent future, employees have also adapted to different working environments and customs, which has also resulted in psychological stress and lethargy for many, as they adapt to the new normal and adjust their personal and professional lives. In this work, data visualization techniques and machine learning algorithms have been used to predict employees stress levels. Based on data, we can develop a model that will assist to predict if an employee is likely to be under stress or not. Here, the XGB classifier is used for the prediction process and the results are presented showing that the method facilitates getting a more reliable model performance. After performing interpretation utilizing XGB classifier it is determined that working hours, workload, age, and, role ambiguity have a significant and negative influence on employee performance. The additional factors do not hold much significance when associated to the above discussed. Therefore, It is concluded that concluded that increasing working hours, role ambiguity, the workload would diminish employee representation in all perspectives.

Link for paper: https://ieeexplore.ieee.org/document/9315726?denied=



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Python Snake Game

Last Updated on May 3, 2021

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This game reminds everyone their childhood memories.

In this snake game, the player has to move the snake to the fruit in order to eat it. The score will increase once the fruit is eaten. Also, the length of the snake will increase if the snake eats the fruit. The game will get over if the snake touches itself.

The turtle and random modules are used in this game project. So as to install these libraries, simply type “pip install turtle” and “pip install random” on the command prompt.

Turtle library allows us to create pictures, diagrams in a virtual form whereas random module gives the value between the given range of it.

There are 3 functions defined in this game which is “change”, “inside function”, and “move” function. In change function, the x-axis and y-axis are defined. In inside function, the logic of the game is written and in the move function, movement to the snake is given.

There are 4 keys mentioned in the code “right, left, up, down”.

If the player presses the right key, the snake will move to right direction, If the player presses the left key , the snake will move to left direction, If the player presses the up key , the snake will move to upward direction, If the player presses the down key , the snake will move to downward direction and if the snake touches itself the game will get over.

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