2r-robotic-arm

To create a simulation of forward Kinematic motion of 2R robotic arm using python 3

analysis_of_fda_medical_device_recall

big-mart-sales-prediction

The aim is to build a predictive model and predict the sales of each product at a particular outlet. Using this model, BigMart will try to understand the properties of products and outlets which play a key role in increasing sales.

capstone-99p-labs

Our primary objective is to contribute to the creation of a future society where individuals can relish in the trifecta of meaningful employment, personal freedom, and unrestricted mobility. By leveraging telematics data and innovative solutions, we aim to pave the way for a society where people can thrive while upholding sustainability principles

car-price-prediction

Problem Statement A Chinese automobile company Geely Auto aspires to enter the US market by setting up their manufacturing unit there and producing cars locally to give competition to their US and European counterparts. They have contracted an automobile consulting company to understand the factors on which the pricing of cars depends. Specifically, they want to understand the factors affecting the pricing of cars in the American market, since those may be very different from the Chinese market. The company wants to know: Which variables are significant in predicting the price of a car How well those variables describe the price of a car Based on various market surveys, the consulting firm has gathered a large data set of different types of cars across the America market. Business Goal We are required to model the price of cars with the available independent variables. It will be used by the management to understand how exactly the prices vary with the independent variables. They can accordingly manipulate the design of the cars, the business strategy etc. to meet certain price levels. Further, the model will be a good way for management to understand the pricing dynamics of a new market.

cassandra-demo

This repo is created for Data Center Scale computing presentation on Cassandra database

churn-chronicle-unraveling-customer-loyalty-mysteries

A telecom firm which has collected data of all its customers. The main types of attributes are: Demographics (age, gender etc.) Services availed (internet packs purchased, special offers taken etc.) Expenses (amount of recharge done per month etc.) Based on all this past information, you want to build a model which will predict whether a particular customer will churn or not, i.e. whether they will switch to a different service provider or not. So the variable of interest, i.e. the target variable here is ‘Churn’ which will tell us whether or not a particular customer has churned. It is a binary variable - 1 means that the customer has churned and 0 means the customer has not churned

credit_eda

Jupyter notebook for Credit EDA Case study

curve-fitting

The curve for specific heat as a function of temperature and it will be plotted and the plot will be compared with the actual plot. The specific heats at different temperature will be provided as inputs

data-driven-strategies-for-supply-chain-optimization

The market for logistics analytics is expected to develop at a CAGR of 17.3 percent from 2019 to 2024, more than doubling in size. This data demonstrates how logistics organizations are understanding the advantages of being able to predict what will happen in the future with a decent degree of certainty. Logistics leaders may use this data to address supply chain difficulties, cut costs, and enhance service levels all at the same time.

data-science-hackathon-2022

This repository is created to create and collaborate on tasks of Data Science Hackathon 2022

data-warehouse-design

datacenter-scale-computing

This repository is specifically crafted to serve as a designated storage facility for your homework assignments related to Datacenter-Scale Computing. It provides a seamless and centralized platform for storing, managing, and collaborating on homework tasks.

dsa-linkedlist-implementation

This repository is created to demonstrate and implementation of Linked list to

flight-fare-prediction

Reference is Taken from "Live- Implementation Of Flight Fare Prediction Web App Project With Deployment" from Krish Naik Youtube Channel

hello-world

housing-prices-predictions

A home buyer to describe their dream house, and they probably won't begin with the height of the basement ceiling or the proximity to an east-west railroad. But this playground competition's dataset proves that much more influences price negotiations than the number of bedrooms or a white-picket fence.

humanitarian-aid

HELP International is an international humanitarian NGO that is committed to fighting poverty and providing the people of backward countries with basic amenities and relief during the time of disasters and natural calamities. It runs a lot of operational projects from time to time along with advocacy drives to raise awareness as well as for funding purposes. After the recent funding activity, they have been able to raise around $ 10 million. Now the CEO of the NGO needs to decide how to use this money strategically and effectively. The significant issues that come while making this decision are mostly related to choosing the countries that are in the direst need of aid. And this is where you come in as a data analyst. Your job is to categories the countries using some socio-economic and health factors that determine the overall development of the country. Then you need to suggest the countries which the CEO needs to focus on the most.

imdb-movies

Data for the 100 top-rated movies from the past decade along with various pieces of information about the movie, its actors, and the voters who have rated these movies online. we will try to find some interesting insights into these movies and their voters, using Python.

impact-of-covid-19-on-food-production-and-humans

This study aims to gain insight into the Impacts of COVID-19 on food production resulting in human life around the world. Production of food in developed and developing countries compared to other countries. Also, COVID-19 took many lives and created complications for others

insurance-premium-prediction

To give people an estimate of how much they need based on their individual health situation. After that, customers can work with any health insurance carrier and its plans and perks while keeping the projected cost from our study in mind. I am considering variables as age, sex, BMI, number of children, smoking habits and living region to predict the premium. This can assist a person in concentrating on the health side of an insurance policy rather than the ineffective part

insurance_prediction_updated

To give people an estimate of how much they need based on their individual health situation. After that, customers can work with any health insurance carrier and its plans and perks while keeping the projected cost from our study in mind. I am considering variables as age, sex, BMI, number of children, smoking habits and living region to predict the premium. This can assist a person in concentrating on the health side of an insurance policy rather than the ineffective part

intelligrade-insights-your-ai-compass-for-academic-excellence

"Student Performance Indicator" is a data-driven project delving into factors like gender, race, parental education, lunch type, and test prep to understand their influence on academic performance.

lead-scoring-case-study

Jupyter notebook for Lead Scoring Case Study

littlelemon

This repository is created for Meta Backend Developer Capstone

ml-exam

This repo is created for ML Final Exam

mnist-digit-recognition

MNIST Digits - Classification Using SVM** Objective We will develop a model using Support Vector Machine which should correctly classify the handwritten digits from 0-9 based on the pixel values given as features. Thus, this is a 10-class classification problem. Data Description For this problem, we use the MNIST data which is a large database of handwritten digits. The 'pixel values' of each digit (image) comprise the features, and the actual number between 0-9 is the label. Since each image is of 28 x 28 pixels, and each pixel forms a feature, there are 784 features. MNIST digit recognition is a well-studied problem in the ML community, and people have trained numerous models (Neural Networks, SVMs, boosted trees etc.) achieving error rates as low as 0.23% (i.e. accuracy = 99.77%, with a convolutional neural network). Before the popularity of neural networks, though, models such as SVMs and boosted trees were the state-of-the-art in such problems. We'll first explore the dataset a bit, prepare it (scale etc.) and then experiment with linear and non-linear SVMs with various hyperparameters. We'll divide the analysis into the following parts: Data understanding and cleaning Data preparation for model building Building an SVM model - hyperparameter tuning, model evaluation etc

mri-stylegan-transforming-medical-imaging

Style Transfer using Generative Adversarial Networks (GAN) Project description- To ensure a better diagnosis of patients, doctors may need to look at multiple MRI scans. What if only one type of MRI needs to be done and others can be auto-generated? - Different MRIs are required for different abnormalities. A single type of MRI may not be sufficient for the diagnosis of an abnormality. Additional MRIs might enhance the accuracy of diagnosis, leading to better treatment of the patient. but Access to different imaging techniques is difficult and expensive. Moreover, doctors may advise getting one type of MRI to be done at a time, which makes it a time-consuming process. with the help of an exciting tool in the deep learning domain, which is known as Generative Adversarial Networks or GANs. - Generative Adversarial Networks (GANs) have been used for generating deepfakes, new fashion styles and high-resolution pictures from the low-resolution ones. - GANs can be used in the field of medical science, for instance, to create a different type of MRI from an existing one. a particular variant of GANs, called CycleGAN, is used to translate the style of one MRI scan into another, such as T1-weighted to T2-weighted or vice versa.

multi-task-learning-for-predictive-maintenance-applications-on-class-imbalance-data

The aim of this study is to determine the machine failure by construction of classifier model on predictive maintenance dataset. The class imbalance data compromise the performance of the constructed model and this is addressed by assessing the oversampling methods with Multi-Task Learning (MTL)architecture. Also, to gauge the performance of auxiliary learning towards the advancement of the primary task learning.

newton-rapson-method

An air-cushion vehicle or ACV also known as A hovercraft, is an amphibious craft capable of travelling over land, water, mud, ice, and other surfaces. An air-cushion vehicle which is used to break ice layers on the surface of rivers, lakes & even on the land in polar countries. This vehicle uses air pressure to create cracks in the ice surface & then the crack propagates in the direction where there is least resistance. To create a crack in the ice-surface minimum air pressure is required to be exerted by the vehicle. E.R. Muller presented an equation with few variables to calculate the pressure. Muller’s equation can be solved using Newton- Rapson Method.