FoodHub Order Analysis using Python
Embedded Files
The food aggregator company has stored data on orders made by registered customers on their online portal. They want to analyze this data to draw actionable insights that can help improve their business. As a Data Scientist hired by the company, you are tasked with answering some key questions to aid this analysis. Perform data analysis to find solutions to these questions that will help the company improve its business.
The food aggregator company has stored data on orders made by registered customers on their online portal. They want to analyze this data to draw actionable insights that can help improve their business. As a Data Scientist hired by the company, you are tasked with answering some key questions to aid this analysis. Perform data analysis to find solutions to these questions that will help the company improve its business.
Skills & Tools Covered: Exploratory Data Analysis (Variable IdentificationUnivariate analysis, Bi-Variate analysis)Python
INN Hotels
Course: Supervised Learning - Classification
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.
Skills & Tools: Exploratory Data Analysis, Data Preprocessing, Logistic Regression, Multicollinearity, AUC-ROC Curve, Decision Tree, Pruning
ReneWind
Course: Model Tuning
"ReneWind" is a company working on improving the machinery/processes involved in wind energy prod using machine learning and has collected data on generator failure of wind turbines using sensors. The objective is to build various classification models, tune them, and find the best one that will help identify failures so that the generator can be repaired before failing/breaking and the overall maintenance cost of the generators can be brought down.
"ReneWind" is a company working on improving the machinery/processes involved in wind energy prod using machine learning and has collected data on generator failure of wind turbines using sensors. The objective is to build various classification models, tune them, and find the best one that will help identify failures so that the generator can be repaired before failing/breaking and the overall maintenance cost of the generators can be brought down.
Skills & Tools: Up and downsamplingRegularizationHyperparameter tuning
CONDURA II |MATAMOROS, TAMPS 1994-1995 ACHIEVEMENTS
A team of 6 people was assigned by Chrysler to inspect a product called the sandwich using random sampling in certain critical regions. This process was conducted for 6 weeks, with data generated and analyzed using Freelance 123. Insights were obtained to improve the product process, which resulted in changes to the design of the item and consequently the parameters of the software used. The changes were made with the aid of the Software Engineer, Production, and Quality Control teams. The results were analyzed by myself and a peer, with the help of a Quality Engineer.
Kaggle Platform
Expectations don't always match reality and energy consumption isn’t immune. When the energy expected to be used doesn't line up with the actual energy used or produced, this energy imbalance causes logistical and financial problems for energy companies. Prosumers – those who both consume and generate energy – contribute a large part of the energy imbalance.
Techniques: Times Series
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