lamia89/ReneWind-project

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lamia89/ReneWind-project

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The objective is to build various classification models, tune them and find the best one that will help identify failures so that the generator could be repaired before failing/breaking and the overall maintenance cost of the generators can be brought down.

EasyVisa-project

Analyze the data of Visa applicants, build a predictive model to facilitate the process of visa approvals, and based on important factors that significantly influence the Visa status recommend a suitable profile for the applicants for whom the visa should be certified or denied.

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Startup-USA-DA

Startups in USA data analysis instructed by Mustafa Othman

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Trade-Ahead-project

Analyze the stocks data, grouping the stocks based on the attributes provided, and sharing insights about the characteristics of each group.

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Sample-Retail--GRIP

This data set includes information about a superstore sales, profit and location covering the United states

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ReCell-project

Analyze the used devices dataset, build a model which will help develop a dynamic pricing strategy for used and refurbished devices, and identify factors that significantly influence the price.

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Case-Study-1-

We're going to investigate this dataset on physicochemical properties and quality ratings of red and white wine samples.

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WeRateDogs-Twitter-archive

The dataset that we will be wrangling (and analyzing and visualizing) is the tweet archive of Twitter user @dog_rates, also known as WeRateDogs. WeRateDogs is a Twitter account that rates people's dogs with a humorous comment about the dog. These ratings almost always have a denominator of 10. The numerators, though? Almost always greater than 10. 11/10, 12/10, 13/10, etc. Why? Because "they're good dogs Brent." WeRateDogs has over 4 million followers and has received international media coverage.

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Breast-Cancer-ML-model

Predicting if the cancer diagnosis is benign or malignant based on several observations/features. inctructed by Dr.Ryan Ahmed

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Foodhub

The food aggregator company has stored the data of the different orders made by the registered customers in their online portal. They want to analyze the data to draw some actionable insights for the business.

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FinTech-app-ML

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Ford-GoBike-data

In this project part, we will conduct an exploratory data analysis on a dataset of your choice.We'll Use Python data science and data visualization libraries to explore the dataset’s variables and understand the data’s structure, oddities, patterns, and relationships.Ford GoBike System Data: This data set includes information about individual rides made in a bike-sharing system covering the greater San Francisco Bay area.

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A-B-test-e-commerce-website

For this project, we will be working to understand the results of an A/B test run by an e-commerce website. The company has developed a new web page in order to try and increase the number of users who "convert," meaning the number of users who decide to pay for the company's product. Our goal is to work through this notebook to help the company understand if they should implement this new page, keep the old page, or perhaps run the experiment longer to make their decision.

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US-Bikeshare-data

In this project, you will use data provided by Motivate, a bike share system provider for many major cities in the United States, to uncover bike share usage patterns. We will compare the system usage between three large cities: Chicago, New York City, and Washington, DC.

Fashion-Business-ML

Fashion training set consists of 70,000 images divided into 60,000 training and 10,000 testing samples. Dataset sample consists of 28x28 grayscale image, associated with a label from 10 classes. Instructed by DR.Rayan Ahmed

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TMDb-movies

This data set contains information about 10,000 movies collected from The Movie Database (TMDb), including user ratings and revenue. ● Certain columns, like ‘cast’ and ‘genres’, contain multiple values separated by pipe (|) characters. ● There are some odd characters in the ‘cast’ column. Don’t worry about cleaning them. You can leave them as is. ● The final two columns ending with “_adj” show the budget and revenue of the associated movie in terms of 2010 dollars, accounting for inflation over time.

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Visulisation-Case-study-Diamonds-data

In this case study, we'll be working with a dataset regarding the prices and attributes of approximately 54,000 round-cut diamonds. we'll go through the steps of an explanatory data visualization, systematically starting from univariate visualizations, moving through bivariate visualizations, and finally multivariate visualizations. Finally, we'll work on polishing up selected plots from the analysis so that their main points can be clearly conveyed to others.

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E-news-Express-Project

This project used statistical analysis, a/b testing, and visualization to decide whether the new landing page of an online news portal (E-news Express) is effective enough to gather new subscribers or not.

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Case-Study-2-Fuel-economy

The fuel economy of an automobile is the fuel efficiency relationship between the distance traveled and the amount of fuel consumed by the vehicle. Consumption can be expressed in terms of volume of fuel to travel a distance, or the distance travelled per unit volume of fuel consumed.

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INN-Hotels-project

Analyze the data of INN Hotels to find which factors have a high influence on booking cancellations, build a predictive model that can predict which booking is going to be canceled in advance, and help in formulating profitable policies for cancellations and refunds.

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