Data Collection for AI and Machine Learning

Statswork- An all-in-one solution for your data-driven problems.
We offer exceptional data collection services for AI and ML that outperforms our competitors.

Our Capabilities

We provide data collection services for AI and ML model enhancement across various organisations to uplift their efficiency and productivity by delivering high-quality AI training data, including text, image, audio, and video.

Industries use AI training data to train their ML models, as it trains the model to various scenarios and prepares it beforehand. Poor quality data will lead to an ineffective model, resulting in failure.

However, Statswork has a team of experts that manages a global workforce of data collectors to gather training data for your Machine Learning models. We can access a wide variety of data from different age groups, demographics, educational backgrounds and ethnicity.

Our service offers a world-class and reliable training dataset to its clients. Ranging from training audio dataset to high-quality video training data sets, handwritten and digital datasets across various languages.

Statswork is well-equipped to help you bring more out of your AI models. Our team of data science consultants are highly qualified experts spread across the globe, and you can be assured of the quality and on-time delivery of your AI project. Our data scientists apply the best approach (e.g., data discovery, data augmentation and data generation) to find dataset that can be used to train ML models.

For training your AI and ML models, we retrieve all kinds of data that makes them gain learned behaviour in a resourceful way.

Text Data Collection Services

To build machine learning solutions capable of understanding the intricacies of human language, large quantities of structured text data is required. Gathering sufficient high quality NLP data is the first step in solving any language-based machine learning problems.

Image Data Collection Services

Your ML algorithms need a lot of datasets to effectively recognize pictures/images Real images. However, the image set that you require must be at right volume, and best match the requirements to carry out the training.

Speech Data Collection Services

Statswork collects end-to-end speech data from high-quality studio recordings in various aspects like languages, dialects, tones, pronunciations. This also includes specific dynamic requirements, like from inside a car to a dinner party.

Video Data Collection Services

With our data collection experts, we collect finest video datasets that reliable and ideal for training Machine Learning models and fine tune them for a specified purpose. The applications range from object detection, facial analysis, activity recognition, etc.

Synthetic Data Collection Services

Synthetic data with labels are being used more and more in ML because it’s cheap and flexible. We provide synthetic data generation service that allows companies to generate unlimited synthetic data that is realistic and representative of real data.

Crowdsourcing Data Collection

Crowdsourcing data collection helps research companies, consulting firms, data analysts and other development experts to gain diverse data on a single phenomenon which adds depth to your research findings.

Our unique selling point is that we provide an entire package of services that you can choose to utilise either fully or partially. Our specialisations include but not limited to the following.

Statswork’s image data collection services delivers high-resolution and contextually relevant visual data to power advanced AI and ML models. Our capabilities extend across various domains, including medical imaging, agricultural monitoring and more. They provide detailed visuals that support accurate analysis and decision-making.

Our NLP data collection services are designed to build robust language models that can accurately process and understand human language. We combine qualitative insights with structured data to improve language comprehension and interaction. Such nuanced approach will differentiate our methods from traditional ones.

Our best AI models working in real-world environments have the goal of attaining contextual sophistication, to make interaction comprehensible. It improves the cross-application engagements from simple chatbots to profound analytical queries with focus and detail for advanced automation.

We utilise multiple deep learning models to empower your AI systems, driving towards more efficiency and improved accuracy. Our Neural Networks help the models to learn autonomously to make organic decisions. This transforms your data into valuable insights, leading to an improved processing through advanced decisions.

These examples speak about our excellence in organising the right data for each of these projects.

Hand X-Ray Data Collection and Analysis.

To contribute to deep learning image processing, we have been able to assemble hand X-ray images with our team. We developed a detailed procedure to collect adequate and efficient data which gave highly accurate outputs.

Handwriting Data Collection

For the development of OCR and Handwriting recognition models, we collected various handwritten samples. The data ranged across different ages and gender, different languages and more importantly, different writing styles.

Dehazing Image Data Collection

We captured hazy images in different settings and dynamics to feed dehazing algorithms. For performance comparison, we used PSNR and the SSIM values to measure the object’s quality. It significantly improved the model performance in adverse working conditions.

Evaluation of Algorithms

We also undertook a series of tests and validation of the algorithms from the AI and ML domains using a wide variety of datasets. Our assessments included safe test strategies and numerous ways to measure the use of algorithms. We were able to provide a complete report in terms of accuracy, recall values, data privacy and security.

HSI Brain Image Data Acquisition

Hyperspectral imaging or HSI is used in the study of the brain and medical investigation where we took images of the brain across the full spectrum of light. This helped us in discovering as well as categorizing various types of brain tissues accurately. We also implemented 3D Convolutional Neural Networks (3D CNNs) to improve the diagnostic outcome and therapeutic procedures.

Facial Image Data Collection

We have acquired high quality facial image data for training models in facial recognition and emotion detection. Some of the steps we took were to gather various HD pictures in different lighting environment and perspectives with different people from different ethnic group, age, gender and most of all, ensuring that the security and privacy of our sources’ were maintained.

Predicting Hospital Readmission

Being oriented on the value-based care delivery, we aimed at creating detailed predictive models to find out readmission candidates. This helped them to formulate specific strategies to minimize readmissions while enhancing the lives of patients.

Acoustic Data Collection

We collected acoustic samples in an extensive range of dB levels for training different AI systems for audio and noise identification. Our wide-ranging datasets are intended to assist with development of these fields.

Semantic Language Data Collection

Specifically, our team gathered a great number of natural language samples to improve the models. We trained and fine-tuned models with the collected data that made it possible for them to operate optimally on the demand input from users.

Labeling and Annotation

We have offered accurate labeling and annotation services which are vitally important for the efficacy of AI and ML models. Thus, our advanced techniques improve data labeling and annotation procedures and thereby increase the accuracy of the models.

Financial Data Collection

We provided diverse financial information sets for application of AI and ML to compile algorithmic trading, fraud detection, and credit rating. The collection of data along with our innovative solutions were ideal for more complex systems within the financial industry.

Agricultural Data Collection

We provide the finest data collection service for AI and ML that contains all the necessities you need. Our team has qualified experts and skilled professionals who work with passion, rather than being driven by financial gains. We are equally invested in your goals, and we lead you on your way to success.

Technology

Healthcare

Retail

Automotive

Financial Service

Government

Technology

Healthcare

Retail

Automotive

Financial Service

Government

Here’s Why you Should Choose Statswork as Your Ideal Data Collection Service Provider for AI and ML

We provide the finest Data Collection Service for AI and ML that contains all the necessities you need. Our team has qualified experts and skilled professionals who work with passion, rather than being driven by financial gains. We are equally invested in your goals, and we lead you on your way to success.

Data Collection for AI & ML

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Information and internet technology has accepted new web-based facilities that affect every aspect of today’s financial and commercial activity.

Data Collection for AI & ML

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Machine learning has made great progress since its inception and continues to evolve at an exceptional pace. New algorithms that are predicted to shape the future

Frequently Asked Questions

1. What is Data Collection in Machine Learning?

In Machine Learning, data collection or data gathering is collecting the appropriate information to train the model in its function.

2. Why Work with an AI/ML Data Collection Service Provider?

The factors like expertise, efficiency, scalability, compliance, and quality assurance can be provided only by an expert data collection service provider. It also reduces time and effort being spent on collecting and validating them.

3. What Key Considerations Should Be Made When Choosing an AI Data Collection Service?

Consider the necessary factors like data quality, reputation of the provider, their proficiency in tools and preview some of their sample works.

4. How Do You Ensure Data Accuracy and Quality During Collection?

Use validation methods like range checks, format checks and standardize them using automated tools and with expert review

5. Can You Handle Large-Scale Data Collection for AI Projects?

Yes, we handle large-scale data using distributed systems and scalable infrastructure.

What is Data Collection in Machine Learning?

In Machine Learning, data collection or data gathering is collecting the appropriate information to train the model in its function.

Why Work with an AI/ML Data Collection Service Provider?

What Key Considerations Should Be Made When Choosing an AI Data Collection Service?

Consider the necessary factors like data quality, reputation of the provider, their proficiency in tools and preview some of their sample works.

How Do You Ensure Data Accuracy and Quality During Collection?

Use validation methods like range checks, format checks and standardize them using automated tools and with expert review

Can You Handle Large-Scale Data Collection for AI Projects?

Yes, we handle large-scale data using distributed systems and scalable infrastructure.

How Do You Handle Data Pre-Processing for AI and ML Projects?

We clean data, normalize them and transform them for optimal machine learning performance.

What industries do you serve with your AI and ML data collection services?

We offer Data collection services in Healthcare, Finance, Retail, Automotive, manufacturing, Telecom, Agriculture, Entertainment, Education, and Energy.

What are the Data Collection Methods for AI and ML Projects

Depending upon the nature of the data, the collection methods can vary. They are Surveys and questionnaires, web scraping, IoT sensors, existing datasets, and public data sets.

Can you build real-time data processing models?

Yes, we can build real-time data processing models with our advanced data-gathering methods and robust machine learning resources.

What is market research data collection?

Market research data collection is the process of acquiring consumer observational data based on market dynamics.