www.analyticsdrift.com
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It is true that the older the wine, the better it will taste. However, age isn’t the only factor that influences a wine’s flavor. You will use fixed acidity, volatile acidity, alcohol, and density to assess the quality of wine in this project. In this AI project, you’ll create an ML model that can look at a wine’s chemical features and estimate its quality. There are roughly 4898 observations in the wine quality dataset you’ll be utilizing for this project, with 11 independent variables and one dependent variable.
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Enron was one of America’s major energy companies in the year 2000. After being exposed for fraud, it went bankrupt in less than a year. On the positive side, the dataset of emails from Enron was retained. The Enron email dataset consists of 500 thousand emails sent between 150 former Enron workers, the majority of whom were top executives. It’s also the only significant publicly accessible collection of genuine emails, making it more useful for natural language processing.
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This is one of the best AI projects for students to learn about forecasting the price of a property based on data from nearby homes. In this project, interested people can learn how to predict prices on the basis of new data. The Boston housing dataset contains information on various houses in Boston based on criteria such as tax rates, crime rates, and the number of rooms in each property. It’s an exceptional dataset for estimating the values of various Boston homes.
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Working on the Iris Flowers categorization AI project idea is one of the finest ways to experiment with machine learning concepts like classification using the iris flowers dataset. Because iris blooms come in a variety of species, the length of the sepals and petals may be used to differentiate them. This machine learning project aims to sort the flowers into one of three species: Virginica, Setosa, or Versicolor.
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Emojis and avatars have been ingrained in internet conversation, product reviews, brand sentiment, and a variety of other activities. It also resulted in an increase in data science research into emoji-driven storytelling. In this project, you will classify human face emotions using deep learning algorithms to filter and map matching emojis or avatars — similar to how Snapchat creates Bitmoji.
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The MNIST digit classification AI project in Python aims to teach computers how to detect handwritten numbers. Since working with image data is more difficult than flat relational data, the MNIST dataset is ideal for someone who is just getting started in deep learning. You will utilize the MNIST datasets to train your ML model using Convolutional Neural Networks (CNNs) in this project.
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Today, online streaming platforms are a huge hit among the millennials and gen-z. These streaming platforms also offer recommendations on what to watch next, based on a viewer’s past viewing habits and interests. This is accomplished by machine learning, and it may be a fun and simple project for people who have a working knowledge of machine learning algorithms.
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This intriguing AI project idea for beginners may help them understand how to visualize data on the Uber platform. This dataset can help you figure out how to evaluate the rides so that you can make business changes. The ride-sharing app needs to have a superior support system to fix consumer complaints as rapidly as possible, with billions of rides to manage each year.
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One of the commonly known healthcare datasets for AI open source project ideas is Breast Cancer Wisconsin Diagnostic Dataset. The difficulty to discern between benign (non-cancerous) and malignant (cancerous) tumors is a major issue in breast cancer detection. You’ll need to classify whether a tumor is malignant or not based on metrics like “radius mean” and “area mean” of the tumor in the dataset.
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Voice AI is one of the trending concepts in the AI industry. Taking advantage of the demand for sophisticated voice AI algorithms that power voice assistants like Alexa to AI chatbots, you can design a project that employs AI open-source datasets using NLP. The librispeech dataset is an enormous collection of English speech data derived from audiobooks from the LibriVox project.