computer science

List of datasets for machine-learning research

List of datasets for machine-learning research is a computer science topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand List of datasets for machine-learning research rather than just read about it. In short: These datasets are used in machine learning (ML) research and have been cited in peer-reviewed academic journals. Datasets are an integral part of the field of machine learning.

Key takeaways

List of datasets for machine-learning research belongs to computer science; place it in that map before memorising details.
Learn the definition first, then one example that makes the definition concrete.
Connect List of datasets for machine-learning research to a quantity you can measure, compute or draw — that is where exam questions come from.
Reproduce the core statement of List of datasets for machine-learning research from memory before moving on to harder problems.

Reference excerpt

These datasets are used in machine learning (ML) research and have been cited in peer-reviewed academic journals. Datasets are an integral part of the field of machine learning. Major advances in this field can result from advances in learning algorithms (such as deep learning), computer hardware, and, less intuitively, the availability of high-quality training datasets. High-quality labeled training datasets for supervised and semi-supervised machine-learning algorithms are usually difficult and expensive to produce because of the large amount of time needed to label the data. Although they do not need to be labeled, high-quality unlabeled datasets for unsupervised learning can also be difficult and costly to produce. Many organizations, including governments, publish and share their datasets, often using common metadata formats (such as Croissant). The datasets are classified, based on the licenses, into two groups: open data and non-open data. The datasets from various governmental-bodies are presented in List of open government data sites. The datasets are ported on open data portals. They are made available for searching, depositing and accessing through interfaces like Open API. The datasets are made available as various sorted types and subtypes.

List of sorting used for datasets

The data portal is classified based on its type of license. The open source license based data portals are known as open data portals which are used by many government organizations and academic institutions.

List of open data portals

List of portals suitable for multiple types of applications

The data portal sometimes lists a wide variety of subtypes of datasets pertaining to many machine learning applications.

List of portals suitable for a specific subtype of applications

The data portals which are suitable for a specific subtype of machine learning application are listed in the subsequent sections.

Image data

Text data These datasets consist primarily of text for tasks such as natural language processing, sentiment analysis, translation, and cluster analysis.

Reviews

News articles

Messages

Twitter and tweets

Dialogues

Legal

Other text

Sound data These datasets consist of sounds and sound features used for tasks such as speech recognition and speech synthesis.

Speech

Music

Other sounds

Signal data Datasets containing electric signal information requiring some sort of signal processing for further analysis.

Electrical

Motion-tracking

Other signals

Chemical data Datasets from physical systems.

Chemical Reactions with transition states (TS)

OpenReACT-CHON-EFH OpenReACT-CHON-EFH (Open Reaction Dataset of Atomic ConfiguraTions comprising C, H, O and N with Energies, Forces and Hessians) is a 2025 open-access benchmark for machine-learning interatomic potentials.

**RTP set** – 35,087 stationary-point geometries (reactant, transition state and product) drawn from 11,961 elementary reactions, each labeled with density-functional energies, atomic forces and full Hessian matrices at the ωB97X-D/6-31G(d) level. **IRC set** – 34,248 structures along 600 minimum-energy reaction paths, used to test extrapolation beyond trained stationary points. **NMS set** – 62,527 off-equilibrium geometries generated by normal-mode sampling to probe model robustness under thermal perturbations. The collection underpins the study Does Hessian Data Improve the Performance of Machine Learning Potentials? and was used to train and benchmark the machine-learning interatomic potentials reported therein. The dataset itself is distributed under a CC licence via Figshare.

Physical data Datasets from physical systems.

High-energy physics

Systems

Astronomy

Earth science

Other physical

Biological data Datasets from biological systems.

Human

Animal

Fungi

Plant

Microbe

Drug discovery

Anomaly data

Question answering data This section includes datasets that deals with structured data.

Dialog or instruction prompted data This section includes datasets that contains multi-turn text with at least two actors, a "user" and an "agent". The user makes requests for the agent, which performs the request.

Cybersecurity

Climate and sustainability

Code data

Multivariate data

Financial

Weather

Census

Transit

Internet

Games

Other multivariate

Curated repositories of datasets As datasets come in myriad formats and can sometimes be difficult to use, there has been considerable work put into curating and standardizing the format of datasets to make them easier to use for machine learning research.

OpenML: Web platform with Python, R, Java, and other APIs for downloading hundreds of machine learning datasets, evaluating algorithms on datasets, and benchmarking algorithm performance against dozens of other algorithms. PMLB: A large, curated repository of benchmark datasets for evaluating supervised machine learning algorithms. Provides classification and regression datasets in a standardized format that are accessible through a Python API. Metatext NLP: https://metatext.io/datasets web repository maintained by community, containing nearly 1000 benchmark datasets, and counting. Provides many tasks from classification to QA, and various languages from English, Portuguese to Arabic. Appen: Off The Shelf and Open Source Datasets hosted and maintained by the company. These biological, image, physical, question answering, signal, sound, text, and video resources number over 250 and can be applied to over 25 different use cases.

See also Comparison of deep learning software List of manual image annotation tools List of biological databases

References

Worked examples

Example 1 — a first encounter with List of datasets for machine-learning research

Start with the simplest possible case. Write down what List of datasets for machine-learning research claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In computer science, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to List of datasets for machine-learning research before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about List of datasets for machine-learning research ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of List of datasets for machine-learning research

In research: List of datasets for machine-learning research appears in computer science research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry: Engineering practice reuses List of datasets for machine-learning research in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom: List of datasets for machine-learning research is common in secondary-school and first-year university syllabi. It links to neighbouring topics Datasets in machine learning, so understanding it makes those chapters shorter.
In everyday life: Look for List of datasets for machine-learning research outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

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How to study List of datasets for machine-learning research in 20 minutes

Read the reference excerpt below once, without taking notes.
Close the page and write down what List of datasets for machine-learning research means in your own words.
Compare your version with the excerpt and mark what you missed.
Work through the three examples above with pen and paper.
Explain List of datasets for machine-learning research out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is List of datasets for machine-learning research in simple terms?

These datasets are used in machine learning (ML) research and have been cited in peer-reviewed academic journals. Datasets are an integral part of the field of machine learning.

Why does List of datasets for machine-learning research matter?

Because it connects several computer science ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study List of datasets for machine-learning research?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on List of datasets for machine-learning research.