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  • Cupids Wingman Social Dating at Doubble Christina Lubinski

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  • Fender vs Gibson A Gibson Tradition Innovation Diversification Adrien SimonnotLanciaux Danilo C Dantas 2022

    Fender vs Gibson A Gibson Tradition Innovation Diversification Adrien SimonnotLanciaux Danilo C Dantas 2022

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  • Predicting Consumer Tastes with Big Data at Gap Ayelet Israeli Jill Avery 2017

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    In this project, I used neural networks to predict the automobile prices of car manufacturers. Here are the steps to achieve this task: Step 1: Data collection I used two sources for data: The US Bureau of Labor Statistics’ (BLS) Historical Data, and Google Finance. I scraped information from these two sources and transformed it into a database with the features for each car manufacturer. Step 2: Preprocessing Data I cleaned the data and split it into training and testing datasets. I also normalized the data

    Evaluation of Alternatives

    Neural networks have been popularized in recent years, especially in the field of predicting automobile prices. This paper aims to utilize neural networks to predict automobile prices by identifying features associated with different vehicle factors such as engine displacement, power source, transmission, engine type, size, speed, and price. We utilized data from the Automotive Prices database (APB) consisting of 38,000 historical vehicle sales data records, and employed a neural network architecture consisting of five hidden layers with varying depths and connections. In terms of training

    VRIO Analysis

    In recent times, the automobile industry is seeing an unprecedented boom. The number of cars being sold in the country has risen over the years, and there’s no signs of stopping. Automotive companies, both foreign and local, are constantly making improvements, launching new products, and expanding their operations to take advantage of this boom. With all the benefits and possibilities of automobiles in the modern world, there’s still a need to forecast the price changes for specific vehicles in the near future. This task is currently being performed

    SWOT Analysis

    In recent years, the automobile industry has been experiencing rapid growth. This has led to increased competition between automobile companies. Automobile manufacturers use several data sources, such as car sales data and price histories, to forecast demand. In this research project, we predict the price of a new car based on several factors, such as engine size, fuel type, car design, and environmental impact. The study will analyze the accuracy of these predictions using machine learning algorithms such as neural networks. Methodology: To predict the price of a new car Read Full Report