AI & ML Training Data: Best AI & ML Training Datasets & Databases

What is AI & ML Training Data?

AI & ML training data refers to any information that enables the training of machines. It's mostly used by developers and engineers e.g. in training their AI systems to make better predictions. Datarade helps you find the right AI & ML data providers and datasets.Learn more

Recommended AI & ML Training Data Products

50+ Results
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Data collection for AI/ ML training | Data collection for Data Science and Data Analytics | Text , image, audio and document data

by TagX
We provide In-field data collection for speech, image, text, and survey data. ... TagX specializes in data collection for Artificial intelligence, data analytics, and other software solutions
Available for 249 countries
10K images/document
99% %
Starts at
$1,000 / month
Free sample available

Data Collection by Shaip: Text, Audio, Image, Video for AI & ML Training

by ShAIp
/audio data collection for training & improving conversational AI & chatbots. ... As a leader in data collection services, we help our clients source sizable volumes of high-quality training
Available for 213 countries
10 years of historical data
95% match rate
Available Pricing:
One-off purchase
Free sample available

Human emotions datasets for AI & ML model

Each data set is supported by both AI and human review process to ensure labelling consistency and accuracy ... 6,000+ high quality images of mixed-race human face emotion ready for AI & Computer Vision models
Available for 18 countries
30K images
5 years of historical data
Available Pricing:
One-off purchase
Yearly License
Free sample preview
Free sample available

Deeply Korean Read Speech Corpus - Audio AI & ML Training Data

by Deeply
Pairs of Korean speakers reading a script with 3 distinct text sentiments, with 3 distinct voice sentiments, are recorded. The recordings took place in 3 different places, of which the level of rev...
Available for 1 countries
190K records
99% Validity
Pricing available upon request
Free sample available

Automaton AI: ADVIT - Deep Learning Platform (white labeled AI & ML Data)

It is a cost-effective data labeling tool (Reduce AI development cost by 2x, Zero start-up cost). ... Data pre-processing platform and Automated Data labeling platform for annotating Images / Videos / Text
Available for 80 countries
Available Pricing:
Monthly License
Yearly License
10% Datarade discount
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Coresignal | Job Posting Data / Global / The Largest Professional Network, Indeed, Glassdoor + 3 Other Sources / 327M+ Records / Updated Monthly

Job posting data offers insights into the current and historical company hiring activities that make ... At a larger scale of analysis, this data can be leveraged to forecast market trends and predict the growth
Available for 249 countries
327 million records
50 months of historical data
Available Pricing:
One-off purchase
Monthly License
Yearly License
Usage-based
Free sample available
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CustomWeather - Global Historical Hourly Solar Data - 40 Years

Hourly, historical solar data for any global location. Datasets dating back to 1980.
Available for 249 countries
40 years of historical data
Starts at
$80 / purchase
Free sample preview
Free sample available

Data Collection by EPIC Translations: Copywriting, Text & Audio Data Data for AI & ML Training

Our Data Collection services: AI Training Data Crowdsourcing Data Processing Copywriting ... Text Data Collection Audio Data Collection Chatbot Training Data Copywriting Crowdsourcing
Available for 215 countries
50K sentences
12 weeks of historical data
100% match rate
Pricing available upon request
10% Datarade discount
Free sample available
10% revenue share
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Versium REACH - B2C Consumer Address, API, USA, GDPR and CCPA Compliant

by Versium
Add consumer contact data, like address to you augment or refresh list of customers or prospects. ... With Versium REACH’s Contact Append or Contact Append Plus you can add consumer contact data, including
Available for 1 countries
1B Emails
70% Over 70% Match Rate
Starts at
$300 / month
Free sample preview
Free sample available
revenue share

Anti-Spoofing dataset by TrainingData.pro

This makes it a diverse and well-rounded resource for training anti-spoofing models, which need to be ... cut-out printouts Trainingdata’s Anti-Spoofing dataset is a comprehensive resource for anti-spoofing training
Available for 215 countries
44.8K videos and selfies with people
3 years of historical data
97% unique people
Pricing available upon request
Free sample preview
10% Datarade discount
Free sample available

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Discover related ai & ml training data products.
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Bulk access to court records, search and track cases, download court documents, update cases, and more.
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Caeli provides real-time satellite data about the composition of the air. The gases measured in the atmosphere are Nitrogen dioxide(NO2) | Ammonia(NH3) | Met...
248 countries covered
Weather Source's Weather Impact Indices incorporate numerous factors such as climatology to provide a reference for the weather being above or below normal, ...
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Get easy access to legal analytics and the structured state and federal court data you need to build analytics for your own unique use cases.
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Caeli provides real-time satellite data about the composition of the air. The gases measured in the atmosphere are Nitrogen dioxide(NO2) | Ammonia(NH3) | Met...
30K Images
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We provide face detection dataset, including data collection, metadata preparation, and annotation services for all face analysis applications. We provide hi...
200K Images with Annotations
100% Quality assurance
240 countries covered
We collect images of Damaged cars from around the world and create a custom annotations on those images for our customers. Annotations can be customized as ...
327 million records
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Job posting data offers insights into the current and historical company hiring activities that make it possible to build a more complete picture of a compan...
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License patient-level, synthetic EHR data that is built from the statistical distribution of data from U.S.-based hospital EHR systems and is readily accessi...
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License patient-level, synthetic claims data that is built from the statistical distribution of real, U.S.-based healthcare data. Augment the original data b...
3 countries covered
We offer audio data wich includes various topics in different languages like English, Hindi, Arabic, French etc. We have round the clock source of any type o...
100K Documents
100% Quality assured
249 countries covered
We collect invoices, receipts, and payslips from around the world. Customers can also order annotations for OCR applications or classification samples. Ext...
891 Equities
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Evaluate sentiment of mentions related to various asset classes, such as fixed income, foreign exchange, commodities, cryptocurrencies, and equities across 7...
316 Banking and financial institutions equities
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Bank-run evaluates the sentiment of mentions related to bank stocks across platforms like Twitter, Reddit, Telegram, Weibo and Seeking Alpha, providing insig...
891 Equities
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Evaluate the sentiment of mentions related to various asset classes, such as fixed income, foreign exchange, commodities, cryptocurrencies & equities across ...
63 Equities
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Track and quantify the impact of Asian (mainland China, Hong Kong and Taiwan) social media on local stocks. This unique data set generates ALPHA providing a ...
50 Hours
99% Accurate
South Africa covered
50 hours of simulated, unscripted agent-caller dialogue. Domains include: Insurance, Retail, Debt Collection, Travel. 46 participants from Western Cape, No...
50 Hours
99% Accurate
South Africa covered
50 hours of simulated, unscripted agent-caller dialogue. Domains include: Insurance, Retail, Debt Collection, Travel. 63 participants from all South Africa...
Deeply
Based in South Korea
Deeply
We make products that anyone can use with audio AI technology and make people's lives happier with those products.
100%
Human-labeled
100%
Accuracy
datarade.ai - TagX profile banner
TagX
Based in India
TagX
TagX is a Data aggregator working with a wide range of industries. We also help companies in annotating and curate their existing datasets. Contact us today...
GDPR
Compliant
HIPAA
Compliant
Regions
180+
EPIC Translations
Based in USA
EPIC Translations
We have over 1 million human resources located throughout the world ready for your projects.
datarade.ai - Pixta AI profile banner
Pixta AI
Based in Japan
Pixta AI
PIXTA AI provide Japanese-quality data preparation & AI modelling service at local cost for scaling your AI / ML / CV projects.
Accuracy
Up to 99%
Scalable
Any project scale
AI Expert
High expertise
datarade.ai - WayWithWords profile banner
WayWithWords
Based in United Kingdom
WayWithWords
Having produced proprietary speech datasets for customers over the years, Way With Words is now listing its own off-the-shelf datasets in order to evidence o...
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SoundPrint is a data provider offering Restaurant Data, POI Visitation Data, Visit Data, Restaurant Traffic Data, and 6 others. They are headquartered in Uni...

The Ultimate Guide to AI & ML Training Data 2023

Learn about ai & ml training data analytics, sources, and collection.

The use of smart devices, robotics, and applications is becoming ubiquitous, thanks to the era of technological advancements that we live in. From personal, to domestic, to commercial use, artificial intelligence (AI) has become commonplace in our lives.

When we talk about AI, we’re referring to a wide-ranging branch of computer science. AI is concerned with building smart machines that can perform tasks that would otherwise necessitate human intelligence. It’s also been described as an interdisciplinary science, as it involves multiple scientific approaches.

In 2020, almost every developing technological field and discipline is linked to artificial intelligence. This means that a good awareness of AI and machine learning (ML) becomes a more crucial part of life with every passing day - this goes for businesses, especially. One of the main things to understand about AI and ML is that their usefulness very much depends on the data you’re feeding to your algorithms - the Artificial Intelligence and Machine Learning training data. This is the data which will allow you to test how well your AI and ML systems are performing, and train them to perform at their optimum.

What is AI & ML training data?

AI & ML training data is used to train a machine learning algorithm or model. It’s used to make your AI technology smarter, more reliable and more efficient. The data allows you to carry out tests to validate that your AI and ML programmes are performing as an intelligent human would, in terms of how they imitate human learning, reasoning and self-correction. AI & ML datasets are used to enhance how technologies like neural networks perform independent of human input - in other words, how they ‘educate’ themselves.

Before this is possible, however, training data requires some human contribution. This is ‘machine learning’. The degree of human participation required depends on the type of machine learning algorithms that are used and the kind of problem that the AI technology is intended to solve.

In general, machine learning using AI & ML training data can be broken down into the following stages:

Input: This refers to the data that is fed to an AI model.

Feature extraction: This refers to a process that involves a dimensional reduction of the raw data into groups of manageable data that is standardized, characteristic, and machine-understandable. In simple words, feature extraction is the identification of key features of the data for machine learning.

Classification: This process includes predicting the class of given data points that are also known as ‘labels’ or ‘categories’. It entails sorting a given set of data into classes by a computer program and is a supervised learning approach. It also allows the AI model to make new observations or classifications.

Output: This refers to the final reactions that an AI model gives after learning.

Whatever the specific ‘output’ is, AI & ML training data works by providing concrete inputs to the algorithms for learning certain patterns. This ‘teaches’ the algorithms to give equally accurate results when they’re exposed to real-life use.

This process of using AI & ML training data to show an AI machine what it ought to predict is sometimes called data processing, tagging, moderation, transcription, and it involves tagging a dataset with vital features that help train an algorithm. It’s this machine learning process that companies today are using to fuel their algorithms. Artificial intelligence and machine learning training data is therefore crucial to their operations. These operations include object identification, pattern finding, and efficient processing of client/patient data, but there are many other use cases for AI & ML training data which we’ll look into later.

On the whole, the goal of an AI & ML training dataset is to give a business’ AI more automated efficiency with fewer errors.

What are the attributes of AI and machine learning training data?

Training data has many forms and attributes, reflecting the numerous potential applications of machine learning algorithms. AI & ML training datasets can include text consisting of both words and numbers, audio, images, and video. Moreover, they’re available in many formats, such as PDF, HTML, JSON, or spreadsheets.

Broadly speaking, AI & ML training data can be assigned to the following categories:

AI & ML training data can be structured, which means that it’s found in a fixed field within a record or file, e.g. data which is contained in relational databases and spreadsheets.

AI & ML training data can also be unstructured, meaning either that it isn’t intended as a predefined data model or that it isn’t organized in a predefined manner.

Hybrid AI & ML training data also exists, which allows you to make use of a blend of supervised and unsupervised learning.

Attributes of AI & ML training data are labeled or annotated using specific techniques which categorize the data into text, image or video. These labels are used and made suitable for computer vision so that the computer being used to programme the AI machine can recognise the data and the outcome the artificial intelligence should arrive at. By ‘computer vision’, we mean that categorical attributes of the AI & ML data must be changed to a numerical format for the machine learning algorithm to work. These attributes of AI & ML training data vary according to how you want to use it, and the APIs available for this intended use.

What are the sources of AI and machine learning training data?

Because it’s such a versatile data type, the sources of AI & ML training data are numerous, and they largely depend on the specific use case. There are many sources that provide information to be used for open AI & ML datasets. Many of these public datasets are maintained by enterprise companies, government agencies, or academic institutions. For more niche use cases, it’s worth getting in touch with your prospective AI & ML training data provider directly, if you’re keen to know more about the sources they use.

How is AI and machine learning training data collected?

Again, this varies between sources and use cases, but one typical approach used by AI & ML data providers to collect a large amount of data from the web is the deployment of scraping techniques. The raw data is then stored on a server. Artificial intelligence and machine learning data providers offer APIs to their servers, meaning the data can be accessed directly by customers. This means that you can download a data provider’s AI & ML training datasets according to your individual requirements. Synthetic data is also regularly used for AI training. Synthetic data is generated using algorithms as opposed to being collected from real-world events.

How to assess the quality of AI & ML training Data?

Much like other data types, there are things to look out for when purchasing a third-party AI & ML training dataset to ensure that you’re receiving the highest quality information possible. High-quality AI & ML training data is vital for a successful AI and machine learning initiative. It’ll ensure that you produce algorithms that work in real life, and will allow you to mitigate some of the bias inherent in manual data annotations - one of the main reasons companies rely on AI in the first place.

It’s always a good idea to request a sample dataset from your AI & ML data provider before opting for them. When examining this sample, look out for:

Accuracy - The ratio of data to errors. As you’d expect, errors will lead to skewed machine behaviour, so must be avoided!

Completeness - Empty fields. Missing information will leave gaps in your AI machine’s ‘knowledge’.

Precision - How the data is labeled. With precise and detailed the label on a dataset, you can decide exactly how useful it’ll be for your specific needs. Avoid vaguely labeled AI & ML datasets - their training ability is often weak.

Scale - Data coverage. The versatile your dataset, the better coverage it’ll give your programme, meaning it’ll have a more holistic view on the problems it should solve.

Timeliness - Outdated data. For certain industries and use cases in particular, the timeliness of AI & ML data is highly important if you’re to achieve efficient results.

Obviously, when requesting a sample, make sure you specify the intended use case for your data. With so many possibilities for machine learning, you’ve got to be sure that your provider can give you data that’s relevant to your AI initiative! Remember - your output will only be as good as the input.

If you can ensure that your data provider upholds each of these quality aspects, then you can expect high quality artificial intelligence and machine learning productivity in return. Apart from requesting an AI & ML data sample, you can carry out quality assessment by looking for verified data vendors and providers, who have undergone accuracy and reliability audits to guarantee you the best results for your machine learning operations.

Once you’ve got access to your AI & ML training data, you can monitor its performance in-flight. An analytical approach to quality assessment will show you where the data is falling short of your desired training strategy:

Gold sets or benchmark: This method helps to measure the accuracy by comparing the annotations to a gold set or vetted example. It also helps to estimate the extent to which the dataset meets the desired benchmark.

Consensus or overlap: This process is common to measure the consistency and agreement amongst a group of data points or datasets. This is done by dividing the total of agreeing data points by the total number of points. If there’s a consensus between your datasets, that’s a good indicator that they’re high-quality.

What are the use cases for AI & ML training data?

As we’ve said several times in this article, there are countless use cases for AI & ML training data! Let’s have a look at a few examples which showcase how artificial intelligence and machine learning are boosting operation efficiency for all kinds of businesses and organisations:

Smartphone Applications - Machine learning powers most of the features on our smartphone, such as voice assistants, camera object detection, unlocking your phone via facial recognition, and App Store and Play Store recommendations.

Retail - Many retail businesses use artificial intelligence for creating virtual shopping experiences by creating custom recommendations for customers.

Supply chain management - Supply chain, stock, and inventory management across all industries can utilize machine learning to speed up the distribution process and to hand their management systems over to AI-based applications.

Transportation Optimization - The frequency of machine learning in the transportation industry has skyrocketed in the last decade, with companies like Uber, Lyft, and Ola launching themselves to success using AI & ML programmes. The emergence of self-driving cars also attests to the rise of machine learning and AI.

Popular Web Services - Some of our most popular online services use machine learning and AI. For example, Gmail uses a machine learning algorithm that allows us to customize labels. Also, social media platforms like Twitter, Facebook, LinkedIn, use machine learning algorithms to generate a list of people you may know.

Sales and Marketing - Companies are using machine learning to inform their marketing and sales strategies. Amazon, Goodreads, IMDb, MakeMyTrip, StitchFix, and Zomato all use AI and ML to enhance their customer service and audience segmentation

AI allows companies to analyze customer behaviour, and pull out the essential information for marketing to capture the right people. Beside managing day to day tasks, AI-based applications can customize sales and marketing information for clients. AI-based Chatbots is an example that allows businesses to increase consumer satisfaction by making product recommendations for upselling.

It can systematize the creation of pricing models for distinct market segments such as cutting out A/B testing, which increases your understanding of what works for your company in a shorter time span.

Security - Businesses are using machine learning to analyze threats better and respond to adversarial attacks. For example, Google uses machine learning to make CAPTCHA security tests.

Finance - There are tons of use cases of machine learning in finance. In the case of credit card transactions, machine learning algorithms can identify fraudulent transactions and flag them so the bank can connect with the customers immediately to check if they made the transaction.
Banks are also using AI & ML training data to reduce their reliance on manual labor, such as developing more precise credit scoring methods and systematizing manual management responsibilities.

AI for Health Care - Machine learning is used in the healthcare industry for many daily tasks, including personal health care assistants and personalized X-ray readings. The use of such data for medical hardware is an especially popular use case. For example, some hospitals use robotic-powered devices to execute surgeries that operate according to artificial intelligence.

The creation of automated medical records is another use case. It not only decreases the use of paper but also makes it convenient to access and keep track of the records while avoiding human error at the same time.

Natural Language Processing - It has become possible to interact with any computer that fully understands natural, spoken language. This allows for a better user experience for different applications.

Vision System - Vision systems understand and interpret the visual input straight on your computer, such as logo recognition. This can include aircraft which take photographs which can later be used as sources of geospatial information, or for mapping certain areas. Doctors make the use of a clinical expert system for diagnosing the patient. Police can also use this computer software, which can identify the criminal face with the stored portrait as made by the forensic artist.

Education - AI learning is of particular benefit for educational facilities. It can be used to create scheduling systems which organize parent teacher meetings, as well as other school activities.

For all of these use cases to work in practice, a rigorous AI & ML training programme has to be implemented. And for this programme to have the desired outcome, AI & ML training data is indispensable.

What are the challenges when buying AI & ML training data?

However versatile a data type it may be, when purchasing, it’s worth being aware of some common challenges with AI training data.

As we’ve seen, AI & ML training data has an amazing range of use cases. The one drawback of this is that you could end up purchasing a dataset that doesn’t cover all of your unique requirements, which would prevent you from achieving the relevant outcome. The best way around this is to communicate all of your needs to your data vendor before you purchase!

This is also the best solution to another problem associated with AI & ML training data: data which is incompatible with the algorithms and systems you’ve already got in place. Obviously, this will limit how efficiently and seamlessly the data can be used to fuel and train your technologies. So it’s crucial that you find out whether your AI & ML provider offers the right kind of integrations for your pre-existing operations and platforms. Otherwise, you risk making a counter-intuitive, ineffective investment.

How is AI and machine learning training data priced?

Given the diversity of all possible use cases of AI and machine learning training data, data providers offer their consumers a wide selection of pricing models, which vary according to your needs. Many providers offer access to their databases via monthly and annual licensing fees to annual cost per prospects. Other custom pricing models can be arranged depending on the size of the AI & ML training dataset you require, and how regularly you’d want data updates.

To sum up…

From the sales department to marketing, retail to medical to HR and finance, every field and division within an industry can set up and operate with improved proficiency without needing too much human interference or intelligence. AI and ML can bring better future opportunities with better profits for the existing system’s management and operation.

However, artificial intelligence and machine learning are not possible without training data. AI & ML training data is the textbook that teaches an AI model to do its allocated job and is used over and over again to sharpen its predictions and advance its success rate. The quality, availability, and relevancy of data directly affect the AI model goals. Where inaccurate or incomplete data sets would train an AI model similar to an illiterate human, the selection of the right data will produce accurate results. The right data is one that is precisely labeled, allowing the AI model to accomplish the best level of accuracy.

For high-quality data sets for machine learning, you can contact data providers that provide machine learning training datasets in different forms according to the adaptability and needs of the project. A good data set service will include text, image, and video annotation services to give the accurately annotated data at affordable rates while ensuring the security of data and privacy until the delivery of the project.

Where can I buy AI & ML Training Data?

Data providers and vendors listed on Datarade sell AI & ML Training Data products and samples. Popular AI & ML Training Data products and datasets available on our platform are Data collection for AI/ ML training | Data collection for Data Science and Data Analytics | Text , image, audio and document data by TagX, Data Collection by Shaip: Text, Audio, Image, Video for AI & ML Training by ShAIp, and Human emotions datasets for AI & ML model by Pixta AI.

How can I get AI & ML Training Data?

You can get AI & ML Training Data via a range of delivery methods - the right one for you depends on your use case. For example, historical AI & ML Training Data is usually available to download in bulk and delivered using an S3 bucket. On the other hand, if your use case is time-critical, you can buy real-time AI & ML Training Data APIs, feeds and streams to download the most up-to-date intelligence.

What are similar data types to AI & ML Training Data?

AI & ML Training Data is similar to Telecom Data, Automotive Data, Research Data, Cyber Risk Data, and IoT Data. These data categories are commonly used for Artificial Intelligence (AI) and Machine Learning (ML).

What are the most common use cases for AI & ML Training Data?

The top use cases for AI & ML Training Data are Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning.

Translations for this page

Datos de IA y Machine Learning (ES)