What does dataset mean?
dataset is a set of data used for research. It can be a raw dataset for statistical analysis, or a dataset extracted from other datasets. It is composed of a set of data structured in a certain way, it can be a table or files in a folder, or it can be data in a database.
What data should be collected in the age of artificial intelligence?
1. Personal attribute data: including gender, age, occupation, education level, address, etc.;
2. User behavior data: including user behaviors such as online search, login, browsing, and purchase;
3. Language data: text, voice, etc.;
4. Image data: including photography, video, etc.;
5. Biological data: such as genes, health status, etc.;
6. Social data: such as social networks, circles, groups, etc.;
7. Spatial data: geographic location, spatial relationship, etc.;
8. Sensor data: such as temperature, humidity, acceleration, etc.;
9. Financial data: such as financial statements, tax data, etc.;
10. Other data: such as logistics, weather, etc.
What does an AI dataset include?
Artificial intelligence data sets refer to various data sets used to build artificial intelligence models, such as images, texts, voices, videos, etc. Their characteristic is that due to their importance in training artificial intelligence models, artificial intelligence datasets generally contain a large number of labeled samples, each of which has a corresponding label to guide the model learning process.
1. Speech datasets: speech datasets for speech recognition, speech datasets for speech synthesis, speech datasets for speech transformation, etc.;
2. Image datasets: image datasets for image recognition, image datasets for image classification, image datasets for image semantic segmentation, etc.;
3. Text datasets: text datasets for text classification, text datasets for text summarization, text datasets for text sentiment analysis, etc.;
4. Video datasets: video datasets for video recognition, video datasets for video classification, video datasets for video semantic segmentation, etc.;
5. Structured datasets: structured datasets for recommendation systems, structured datasets for data mining, structured datasets for machine learning, etc.
Commonly used artificial intelligence datasets:
The following datasets are mainly used in academia:
1. MNIST dataset: The MNIST dataset is a handwritten digit recognition dataset, which contains a total of 60,000 training samples and 10,000 test samples between 0 and 9, and each sample is a 28×28 pixel picture.
2. CIFAR-10 dataset: The CIFAR-10 dataset is an image recognition dataset that contains 60,000 32×32 color images, divided into 10 categories, each with 6,000 images.
3. ImageNet dataset: ImageNet dataset is a large-scale computer vision dataset with 12,000 categories and 14 million pictures of different sizes.
4. LabeledFacesintheWild (LFW) dataset: The LFW dataset is a face recognition dataset that contains 13,233 pictures of different faces, as well as some metadata (gender, age, etc.).
5. UCI Machine Learning Library: UCI Machine Learning Library is a public website that collects a large number of machine learning datasets. There are hundreds of different datasets, covering image recognition, text classification, natural language processing and other fields