Datasets for machine learning practice

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Coupled with the preprocessing, this makes it very smooth and fast to get started with.

datasets for machine learning practice

This dataset provides a comprehensive platform to enhance your skills in data manipulation and model building.

2. Its design is based on the digitized image of a fine needle aspirate of a breast mass. It has more than 1,000 categories of objects or people with many images associated with them. Practically everyone in the field has experimented on it at least once.

It consists of 70,000 labeled images of handwritten digits (0-9).

So, if you are a beginner, you can use the straightforward linear classifier, however, you can also try and practice a deeper network.  

5. This dataset is suitable for building models to predict future stock prices using techniques like ARIMA, LSTM, or other time series forecasting models. Datasets provide the essential rails on which machine learning algorithms ride, helping researchers and developers unravel patterns and create predictive models.

Here are our top 65 datasets for machine learning:

  1. Top 5 Open Dataset Repositories
  2. Top 5 Government Datasets
  3. Top 5 Finance & Economics Datasets
  4. Image Datasets for Computer Vision
  5. Sentiment Analysis Datasets
  6. Natural Language Processing Datasets
  7. Datasets for Autonomous Vehicles
  8. Our Commitment to the AI Community

Open Dataset Repositories

Exploring different datasets is a foundational step in mastering machine learning.

Stroke Prediction Dataset

Link to Dataset

The Stroke Prediction dataset is a valuable tool for predicting whether a patient is likely to suffer a stroke based on various input features. Your objective is to build a model that given an image can accurately predict which breed it is. In addition, this dataset allows for many different models to work well.

Yet still, you may be wondering where to begin and which of the thousands of machine learning datasets to choose.

So, to help you get off to a good start, we have selected the 10 best free datasets for machine learning projects. All these sizes are numerical, which makes it easy to get started and requires no preprocessing. Amazon Reviews Dataset

We are now entering the territory of Natural Language Processing (NLP).

This dataset is ideal for sentiment analysis, recommendation systems, and various text classification tasks. By using these datasets, we will be able to build regression, classification, time series, computer vision, and natural language processing models, providing a comprehensive foundation for your machine learning journey.

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Well, in that case you can explore our machine learning and deep learning courses that are part of the 365 Data Science program. Here are some valuable datasets to enhance your NLP projects:

  • Amazon Reviews: Dataset with over 35 million Amazon reviews for sentiment analysis and more.
  • UCI’s Spambase: Dataset focused on spam, ideal for spam filtering models.
  • Enron Dataset: Collection of senior management email data from Enron for text analysis.
  • Google Books Ngrams: Extensive library of words for language analysis and modeling.
  • Yelp Reviews: Dataset containing 5 million Yelp reviews for various NLP applications.

Datasets for Autonomous Vehicles

Autonomous vehicles require large amounts of top-notch quality datasets to interpret their surroundings and react accordingly.

  • Comma.ai: Dataset featuring 7 hours of highway driving with car’s details.
  • Berkeley DeepDrive BDD100K: Self-driving AI dataset with over 100,000 videos of drives.
  • LISA: Dataset with information on traffic signs, vehicles detection, lights, and trajectory patterns.
  • Oxford’s Robotic Car: UK dataset with repetitions of a single route across different conditions.

These datasets empower AI teams to develop and refine autonomous driving technologies.

Our Commitment to the AI Community

At SmartOne, we’re passionate about the potential of AI and machine learning.

We firmly believe in the power of quality datasets to drive innovation and transformative solutions in this space. The images themselves are 28x28 pixels and are in grayscale (meaning each pixel has 1 numeric value – how “white” it is).