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5 AI Training Steps & Best Practices
AI can boost business performance, but 85% of AI projects fail, often due to poor model training. Challenges such as poor data quality, limited scalability, and compliance issues hinder success. Check out the top 5 steps in AI training to help businesses and developers train AI models more effectively.
Top 10+ Software Testing Best Practices
Detecting software bugs before release is crucial for ensuring project success from user engagement and financial perspectives. The cost of solving bugs in the testing stage is almost seven times cheaper compared to the production stage. However, testing is time-consuming and expensive.
50+ Datasets for ML & AI Models
Data is required to leverage or build generative AI or conversational AI solutions. You can use existing datasets available on the market or hire a data collection service. We identified 50+ datasets to train and evaluate machine learning and AI models.
Reverse Proxy Server vs Proxy Server
A reverse proxy is a type of proxy server that retrieves resources on behalf of a client from a web server. Unlike a forward proxy (which sits in front of clients to protect them from external servers), a reverse proxy sits in front of servers.
Top 7 Sentiment Analysis Challenges
Words are the most powerful tools to express our thoughts, opinions, intentions, desires, or preferences. However, the complexity of human languages constitutes a challenge for AI methods that work with natural languages, such as sentiment analysis. Explore sentiment analysis challenges and ways to improve sentiment analysis accuracy: Top 7 challenges in sentiment analysis 1.
20 Test Automation Case Studies Demonstrating Business Impact
QA teams struggle with slow, manual testing, which often results in higher costs, longer development cycles, and customer dissatisfaction. Transitioning to automated QA testing is the top priority in the software testing environment. To help decision-makers assess the impact of test automation, we analyze 20 case studies highlighting real-world transformations.
Compare Top 5 MLOps vs DataOps Differences
Inspired by DevOps practices, MLOps and DataOps have emerged as critical methodologies for ensuring seamless machine learning and database operations. While both share roots in automation and operational efficiency, the debate around MLOps vs DataOps highlights their distinct roles in IT workflows.
Robotic Process Automation (RPA) in Aviation
The aviation sector, as a whole, can gain from the adoption of RPA tools in areas including airport administration, ticket sales, and aircraft navigation. The aviation industry is ripe for automation thanks to the never-ending flow of data that could be turned into actionable insight.
Model Retraining: Why & How to Retrain ML Models?
Only ~40% ML algorithms are deployed beyond the pilot stage. Such low rate of adoption can be explained with the lack of adaptation to new trends and developments such as economic circumstances, customer habits and unexpected disasters like Covid-19.
Top 4 Methods of Sentiment Analysis in Retail Industry
In 2022, the retail industry surpassed $5 trillion for the first time, indicating a continuing desire to buy and consume.However, meeting an increasing number of customers’ needs, and standing out among competitors require great effort. That’s why retail companies have started to automate their processes to benefit from AI-powered methods even more.