How NLP can increase Financial Data Efficiency
The finance sector is driven to make a significant investment in natural language processing (NLP) in order to boost financial performance by the quickening pace of digitization. NLP has become an...
26 February
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MLOps and ML Data pipeline: Key Takeaways
If you have ever worked with a Machine Learning (ML) model in a production environment, you might have heard of MLOps. The term explains the concept of optimizing the ML lifecycle by bridging the...
24 February
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Implementation of Artificial Intelligence in Gaming
What is AI in Gaming?
AI in gaming is the use of artificial intelligence to create game characters and environments that are capable of responding to a player’s actions in a realistic and d...
23 February
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Intelligent Document Processing Workflow and Use cases
Artificial Intelligence has stepped up to the front line of real-world problem solving and business transformation with Intelligent Document Processing (IDP) becoming a vital component in the glob...
22 February
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How Data Annotation is used for Speech Recognition
Speech recognition refers to a computer interpreting the words spoken by a person and converting them to a format that is understandable by a machine. Depending on the end goal, it is then converted t...
20 February
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AI and Data Annotation for Manufacturing and Industrial Automation
Industrial automation refers to the use of technology to control and optimize industrial processes, such as manufacturing, transportation, and logistics. This can involve the use of automation equ...
19 February
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How Data Annotation is used for AI-based Recruitment
The ability of AI to assess huge data and swiftly estimate available possibilities makes process automation possible. AI technologies are increasingly being employed in marketing and development...
17 February
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The Ultimate Guide to Data Ops for AI
Data is the fuel that powers AI and ML models. Without enough high-quality, relevant data, it is impossible to train and develop accurate and effective models.
DataOps (Data Operations) in Artificial...
16 February
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Data Annotation for Smart Security and Surveillance
Computer vision is a rapidly growing field of artificial intelligence that is revolutionizing the way we interact with technology. It involves the development of algorithms, models, and systems th...
15 February
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Data Annotation: How it Can Boost Your AI Models?
As artificial intelligence (AI) continues to revolutionize various industries, data annotation has become an essential part of the process. Essentially, data annotation involves labeling data to make...
14 February
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Data Annotation Outsourcing: How to choose a reliable vendor
Artificial Intelligence (AI) has rapidly grown and transformed the way businesses operate and interact with their customers. The success of an AI model is heavily dependent on the quality of the...
13 February
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How Data Annotation drives precise AI Video Analytics
In the era of data-driven insights and intelligent automation, video analytics has emerged as a transformative technology, revolutionizing the way we extract valuable information from video data. At the heart of this innovation lies the power of artificial intelligence (AI) and its ability to...
10 February
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Synthetic Data: Description, Benefits and Implementation
The quality and volume of data are critical to the success of AI algorithms. Real-world data collection is expensive and time-consuming. Furthermore, due to privacy regulations, real-world data ca...
09 February
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Synthetic Document Generation for NLP and Document AI
NLP (natural language processing) and document AI are technologies that are quickly developing and have a wide range of prospective applications. In recent years, the usage of NLP and document AI has significantly increased across a variety of industries, including marketing, healthcare, and finance...
08 February
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A Comprehensive Overview of Object Detection Datasets in Computer Vision
Object detection datasets in computer vision refer to collections of labeled images or videos that are specifically curated and annotated for the task of object detection. These datasets are used to t...
07 February
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Data preparation for AI-fueled Geospatial Analysis
Its been ages since businesses, governments, researchers, and journalists are using satellite data that helps understand the physical world and take action. As the geospatial industry evolves, so are the ways in which geospatial professionals use data to solve problems. Satellite imagery contains in...
06 February
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Text Analytics: Unlocking the power of Business Data
Due to the development in the use of unstructured text data, both the volume and diversity of data used have significantly increased. For making sense of such huge amounts of acquired data, businesses...
05 February
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Top 6 Computer Vision applications in Insurance sector
The world of insurance, a massive industry that employs millions, is undergoing a big change thanks to technologies like machine learning and computer vision. In recent times, these technologies have become more common in insurance, with new uses and applications popping up regularly.
Artificial...
03 February
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How Web Scraping leads the way for Ecommerce Insights?
In the ever-evolving realm of e-commerce, the importance of having a profound understanding of the market and an acute awareness of customer demand cannot be overstated. These two factors are like the...
01 February
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Data Collection for Machine Learning and AI
In order to build intelligent applications capable of understanding, machine learning models need to digest large amounts of structured training data. Gathering sufficient training data is the first step in solving any AI-based machine learning problem.
Data collection means pooling data by scrapin...
31 January
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