Machine Learning Testing - AI Testing Services by QASource

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Transform Your Business With AI

If you're looking to take your first step towards digital transformation, AI is your big game changer. QASource has experts who will dive into your current business model and help you implement the best AI testing solutions for your business.

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What Are AI Applications?

AI applications are intelligent systems built on technologies like Deep Learning, Machine Learning, Computer vision, NLP, etc.

AI model’s performance is a combination of data collection, labeling, feature engineering, model training, and re-training.

AI applications are found in a wide range of industries: Finance, Healthcare, Text analytics, Robotics, Speech Recognition, Marketing, Banking, Gaming, Autonomous Vehicles, etc.

Why Is AI Testing Important?

AI is used virtually in every industry to automate monotonous business processes.

AI works well for situations similar to that of training data but its performance is hampered in situations for which the AI model is not well-trained.

Outputs of the AI model are probabilistic and responses of the AI model for a given input can change over time.

Unlike traditional QA, instead of fixed results in tests, evaluation techniques and matrices are required for AI model evaluation and testing.

AI Testing Challenges

Problem of Bias: Data used for training could be skewed or may suffer from class imbalance, which introduces bias in the model.
Extracting Root Cause: Extracting the root cause of a prediction error in AI is generally not possible as an AI model is a combination of training data, labels, algorithms, and training parameters. Therefore, narrowing down the root cause of an error is not easy.
Iterative Learning of Models: Unlike traditional software systems, where once development and thorough QA covering all verification and validation of a feature is done, it does not require retesting until there are some new code changes, AI models need constant re-training on new data. Therefore, AI models need constant evaluation and testing.
Non-deterministic: AI/ML systems are non-deterministic, they can generate different outputs or responses for the same input on different runs. Therefore, the traditional QA approach of verifying fixed expected results does not work here.
Test Scenarios: Generating test scenarios or edge scenarios for AI systems is difficult and needs solutions like metamorphic testing.

Talk to One of Our AI Specialists

We Are the Best at Providing Outsourced QA Services to Help Clients Release Better Quality Software Products

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QASource’s Artificial Intelligence Testing Services

Data Validation

Evaluation of quality of training datasets, including aspects such as bias and variety
Validation of data labels
Exaction and curation of validation and test datasets

AI Model Evaluation and Testing

Model’s prediction result analysis and evaluation
AI model evaluation is based on metrics like confusion matrix, AUC ROC, F1 Score, etc.
Sharing insights and feedback on model behavior to AI model developers

Computer Vision Application Testing

Thorough QA and QC for images or video data ingestion
Testing of data annotations, data labeling, and data ingestion format
Computer vision-based test automation for visual testing

NLP Applications Testing

Testing of NLP models’ recognition and predictions
Speech and NLP models evaluation based on metrics like word error rate (WER), text similarity measures such as cosine similarity, Levenshtein distance, etc

Metamorphic Testing

Test case generation and test results verification based on metamorphic relations, to validate the algorithm’s response to multiple inputs and their expected outputs
Testing metamorphic relations

Non-functional Testing

Data scalability and performance testing for the AI systems
System integration and API Testing
Security Testing

Chatbot Testing

Domain Testing: Chatbots are domain-specific and need to have specificities associated with their domain identified and tested upfront.
Limit Testing: Verification of how a chatbot responds to an irrelevant question and identifying the outcome when a chatbot fails.

Robotics Testing

It is a simulation-based behavior testing that includes debugging an algorithm, testing object detection and response, and testing defined goals.
Testing of hardware availability and unavailability scenarios.

Why Partner With QASource’s AI Testing Team?

Expertise in AI QA services for machine/deep learning applications, NLP, computer vision, speech recognition, and robotics
Computer vision and NLP-powered test automation for AI applications
A dedicated team of QA experts with knowledge of machine/deep learning applications, NLP, and computer vision
A team well-versed in AI workflows, model evaluation, and testing
Nearshore, offshore, and hybrid outsourcing options
Access to state-of-the-art testing facilities, test labs, and tools
Non-billable engineering leadership and US customer support
Access to an advanced technology group constantly improving our automation, database, DevOps, Dev, and IT capabilities

Are You Ready to Take Your Software Product to the Next Level? Let’s Talk.

Speak with One of Our AI Specialists to Learn How we can Help your Team:

QASource exists to help organizations like yours enjoy the benefits of a full QA department without the associated setup cost and hassle. With an emphasis on time-bound delivery and customized solutions, we excel at helping our partners manage the quality of their deliverables while keeping costs low.

QA Services

Get in Touch

Address: 73 Ray St, Pleasanton, CA 94566
Tel: +1.925.271.5555
Email: info@qasource.com
30 Minute Free Consultation

The Power of Artificial Intelligence and Machine Learning Testing

Transform Your Business With AI

What Are AI Applications?

Why Is AI Testing Important?

AI Testing Challenges

We Are the Best at Providing Outsourced QA Services to Help Clients Release Better Quality Software Products