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  1. 3 days ago · Kaggle is a huge community of data scientists and machine learning experts. It brings together over five million registered users, offering them access to thousands of public datasets and code snippets called notebooks. One of the significant advantages of Kaggle is that it’s used by some of the best data scientists globally.

  2. About Dataset. Glaucoma is marked by the dysfunction and loss of retinal ganglion cells (RGCs), leading to structural changes in the optic nerve head, retinal nerve fiber layer (RNFL) thickness, ganglion cell layer, inner plexiform layers, and visual field loss.

  3. Jun 18, 2024 · I'm getting a list with blank spaces equal to the number of files in the respective dataset. I didn't find a mention to anything like that in the internet, so I guess that maybe it should be a recent bug/problem. In addition, I can actually use: !kaggle datasets files <user>/<dataset>.

  4. Jun 26, 2024 · Steps to start a data science project. Define your problem: Clearly state what you want to solve. Gather and clean your data: Prepare it for analysis. Explore your data: Look for patterns and relationships. Hands-on experience is key to becoming a data scientist. Projects help you: Apply what you've learned. Develop practical skills.

  5. Jun 12, 2024 · Kaggle Datasets. Kaggle is known for hosting machine learning and deep learning challenges. The relevance of Kaggle in this context is that they provide datasets, and at the same time provide a community of learners and ML practitioners, whose work shall help us with our progress.

  6. 4 days ago · This Amazon Delivery Dataset provides a comprehensive view of the company's last-mile logistics operations. It includes data on over 43,632 deliveries across multiple cities, with detailed information on order details, delivery agents, weather and traffic conditions, and delivery performance metrics.

  7. Jun 12, 2024 · Kaggle is an online platform that enables data science practitioners to find and publish data sets, explore and build models in a collaborative web-based environment, and participate in competitive challenges to develop predictive models, providing a valuable resource for learning, skill development, and practical experience in the field of data...