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Appen
ClickworkerLionbridgeMindriftOneFormaRemotasksTolokaTelusScale AINo subject matter listed
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VideoWith a solid background in content writing, search engine evaluation, and AI training, I bring over three years of experience in delivering high-quality digital services across global platforms. My work has involved evaluating and optimizing search engine results, developing AI training datasets, and labeling image, text, and video content with high accuracy. I have collaborated with leading companies through platforms such as Appen, Oneforma, UHRS, and Toloka, where I contributed to the improvement of machine learning systems through careful analysis and annotation. I have also worked on Arabic audio transcription projects, demonstrating precision in transcribing and reviewing spoken content, which enhanced language models and voice recognition systems. In addition, I have experience using CVAT (Computer Vision Annotation Tool) to annotate image data for machine learning projects, ensuring accurate object detection and classification. I am also proficient in Microsoft Office tools, which I use regularly to organize, report, and present project outcomes professionally. Beyond my core expertise, I possess strong skills in SEO, advanced web research, copywriting, and data analysis. I am proficient in tools like Canva, Photopea, and various task-specific platforms. These experiences have helped me refine my critical thinking, attention to detail, time management, and problem-solving abilities—key strengths in remote and freelance environments. My approach is driven by a
This HIT app specifically looks at what articles we are matching to which business and asks you to decide if the article should be mapped to this business.
This purpose of this task is to make sure that the address and location shown for a business on
The purpose is to provide instructions on how to evaluate link titles for potential Clickbait and label content in SRT along the different subtypes of Withholding & Sensationalism.
These tasks are split up into 3 groups, the first are user (query) intent to ad evaluations, the 2nd are user (content page) to ad evaluations, and the third include evaluations that don't fit into the first two categories (for example concept to concept (query to keyword) evaluations).
Imagine that you are shopping on Amazon. You will see a search query and (optional) category selected, and one or more products to be judged for relevance to that query. You will need to use one of four labels for each product you see.
B+ , social work
Search engine evaluation, and AI training
