What data should machine learning beginners use?

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What data should machine learning beginners use? [Copy link]

 

What data should machine learning beginners use?

xiaoqian123

Machine learning beginners can use various types of data to learn and practice, depending on your area of interest and learning goals. Here are some common data types for beginners to refer to:

1. Classic datasets :

   • Many classic machine learning datasets can be used for learning and practice, such as:
     • Iris dataset: A classic classification problem dataset that contains features of three different species of irises.
     • MNIST dataset: A dataset for handwritten digit recognition, containing a large number of handwritten digit images and corresponding labels.
     • CIFAR-10 and CIFAR-100 datasets: datasets for object recognition, containing images of objects in 10 or 100 categories.
     • Wine dataset, Boston house price dataset, etc.

2. Open Datasets :

   • There are also many open datasets available, covering a variety of different fields, such as government data, social media data, medical data, etc. You can choose the appropriate dataset to study according to your interests.

3. Sensor Data :

   • You may be familiar with sensor data. You can collect or use some sensor data for machine learning practice, such as accelerometer data, gyroscope data, weather data, etc.

4. Time Series Data :

   • Time series data is common in many fields, such as stock prices in the financial field, temperature data in the meteorological field, etc. You can use time series data to practice tasks such as time series forecasting and trend analysis.

5. Image data and video data :

   • Image and video data are very important in the field of computer vision. You can use various image datasets to learn and practice tasks such as image classification, object detection, image generation, etc.

6. text data :

   • Text data is very important in the field of natural language processing. You can use various text datasets to learn and practice tasks such as text classification, sentiment analysis, and text generation.

No matter which type of data you choose, it is important to ensure that the data is of good quality and that you understand the characteristics and context of the data. By practicing with real data sets, you can better understand the application and effects of machine learning algorithms and improve your skills.

qiuxubiao

For machine learning beginners, it is very helpful to use classic and easy-to-understand datasets. Here are some commonly used datasets for beginners:

1. Iris Dataset :

   • Contains the measurement data of the sepals and petals of three different species of irises. This is a classic classification problem dataset, suitable for learning classification algorithms.

2. Handwritten digit dataset (MNIST Dataset) :

   • Contains a large number of handwritten digit images, each of which is labeled with the corresponding digit. This dataset is often used for learning and practicing image classification and recognition.

3. Boston Housing Dataset :

   • It contains house prices and various characteristics of different areas in Boston, such as the average number of rooms in a house, the age of the house, etc. It is suitable for learning and practicing regression analysis and house price prediction models.

4. Wisconsin Breast Cancer Dataset :

   • Contains some characteristic data of breast cancer tumors, which can be used for learning and practicing classification models, such as predicting whether a tumor is benign or malignant.

5. Movie ratings dataset (MovieLens Dataset) :

   • Contains user ratings of movies, which is suitable for learning and practicing recommendation systems and collaborative filtering algorithms.

These datasets are classic and commonly used, with rich documentation and materials for reference, suitable for beginners to explore the basics of machine learning algorithms and models. Choose a dataset of interest, combine it with the corresponding tutorials and materials, and start your machine learning journey!

Jobby8

As a beginner in machine learning, you can use some classic and widely used datasets for learning and practice. These datasets are usually standardized, cleaned, and have rich documentation and materials for reference. The following are some common datasets suitable for beginners:

1. Iris Dataset :

   • This is a classic classification problem dataset that contains measurements of the sepals and petals of three different species of irises. It is a simple and easy-to-understand dataset suitable for learning classification algorithms.

2. Handwritten digit dataset (MNIST Dataset) :

   • This is a dataset containing a large number of handwritten digit images, each of which is labeled with the corresponding digit. It is often used for learning and practicing image classification and recognition.

3. Boston Housing Dataset :

   • This dataset contains house prices and various characteristics in different areas of Boston, such as the average number of rooms in a house, the age of the house, etc. It is often used for learning and practicing regression analysis and house price prediction models.

4. Wisconsin Breast Cancer Dataset :

   • This dataset contains some characteristic data of breast cancer tumors, which can be used for learning and practicing classification models, such as predicting whether the tumor is benign or malignant.

5. Movie ratings dataset (MovieLens Dataset) :

   • This is a dataset containing user ratings of movies, suitable for learning and practicing recommendation systems and collaborative filtering algorithms.

These data sets can help you become familiar with different types of machine learning problems, understand common data preprocessing and feature engineering methods, and master common machine learning algorithms and models. At the same time, you can also choose other suitable data sets for learning and practice according to your interests and needs.