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arya.ai-assesment

assignments

california-housing-price-prediction

Problem Statement : The US Census Bureau has published California Census Data which has 10 types of metrics such as the population, median income, median housing price, and so on for each block group in California. The dataset also serves as an input for project scoping and tries to specify the functional and nonfunctional requirements for it. Problem Objective : The project aims at building a model of housing prices to predict median house values in California using the provided dataset. This model should learn from the data and be able to predict the median housing price in any district, given all the other metrics. Districts or block groups are the smallest geographical units for which the US Census Bureau publishes sample data (a block group typically has a population of 600 to 3,000 people). There are 20,640 districts in the project dataset.

diabetes_prediction_app

diamond_price_predictions

einsite-computer-vision-challenge

fabric-defect-detection

healthcare_capstone-project

hello-world

Welcome to GitHub

himanshu0221

human-detection-in-an-aerial-video

load-forecasting

loan-default-prediction

The Bank Indessa has not done well in last 3 quarters. Their NPAs (Non Performing Assets) have reached all time high. It is starting to lose confidence of its investors. As a result, it’s stock has fallen by 20% in the previous quarter alone. After careful analysis, it was found that the majority of NPA was contributed by loan defaulters. With the messy data collected over all the years, this bank has decided to use machine learning to figure out a way to find these defaulters and devise a plan to reduce them. This bank uses a pool of investors to sanction their loans. For example: If any customer has applied for a loan of $20000, along with bank, the investors perform a due diligence on the requested loan application. Keep this in mind while understanding data. In this challenge, you will help this bank by predicting the probability that a member will default.

machine-predictve-maintenance-app

minutes_meeting_generator

ml_pipeline_project

object-detection-webapp

perform_facial_recognition_with_deep_learning_in_keras_using_cnn

project-template

pubg--exploaratory-data-analysis

task-1-predict-the-percentage-of-an-student-based-on-the-no.-of-study-hours.

Data Science and Business Analytics Task-1 (Predict the percentage of an student based on the no. of study hours).

task-2-iris-dataset

Prediction using Unsupervised ML (Task-2 Predict the optimum number of clusters and represent it visually.)

task-3-exploratory-data-analysis---retail

Perform ‘Exploratory Data Analysis’ on dataset ‘SampleSuperstore’

task-5-exploratory-data-analysis---sports

Exploratory Data Analysis (Task-5 Exploratory Data Analysis’ on dataset ‘Indian Premier League') using Python Created Storyboard.