Hasan Selman
Author Archive

Hasan Selman

Machine Learning Engineering: The Science Of Building Reliable Ai Systems
Machine LearningArtificial IntelligenceFeatured

Machine learning engineering aims to apply software engineering and data science methods to turn machine learning models into usable functions for products and consumers. Artificial intelligence technology is created using machine learning engineering with massive data sets. Machine learning engineering develops AI systems and algorithms to learn and ultimately make

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Is Dataops More Than Devops For Data?
Data ScienceData Science 101FeaturedTopicsUnderstanding Big Data

DataOps and DevOps are collaborative approaches between developers and IT operations teams. The trend started with DevOps first. This communication and collaboration approach was then applied to data processing. Both methods argue that collaboration is the primary approach for application development and IT operations teams, but they target different operation

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What Is An Automation Engineer
Data ScienceFeaturedIndustrial Goods & ServicesIndustryInternet of ThingsTechnology & IT

An automation engineer’s day-to-day tasks include designing and implementing technological processes that automate various activities. Automation technology is currently being used in various business, IT, and development processes, which has prompted organizations to seek these professionals to create, test, and implement automation technologies. Automation is the use of data from

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Erp Vs Crm A Comprehensive Comparison
BI & AnalyticsData ScienceFeaturedTopics

Delving into ERP vs CRM, one needs to make a detailed comparison to decide as Enterprise Resource Planning (ERP) and Customer Relationship Management (CRM) are the most common software tools businesses use to automate core business activities. ERP connects a company’s financial and operational systems to a central database, allowing

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How To Secure Iot Networks?
Internet of ThingsCybersecurityFeatured

Internet of Things (IoT) solves the critical problems of many sectors, from production to health, from transportation to logistics. However, the increasing security risks for IoT networks require caution when taking advantage of connected devices. Interconnected IoT objects are not the same devices, objects, or services. Each object has a

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Artificial Intelligence Call Center Ai'S Impact On The Customer Service
Data ScienceArtificial IntelligenceFeaturedRetail & Consumer

The Artificial Intelligence Call Center era has begun. Call centers have long used cutting-edge technology, from call routing systems that sent consumers to the first available agents to interactive voice response (IVR) systems that millions of customers interact with today. With artificial intelligence (AI) gaining traction in the early 2000s,

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What Nanomachines Promise For The Humanity
HealthcareFeaturedIndustryInternet of Things

Nanomachines, also known as molecular machines or nanites, are molecular robots not larger than a strand of human hair. They can be programmed to carry out tasks in biological systems. Biologists frequently use these molecular machines to perform DNA replication and ATP synthesis tasks. Nanorobotics is one of the most

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How Technology Changes Enterprise Risk Management
TopicsBig DataFeatured

Enterprise Risk Management (ERM) refers to businesses’ techniques and procedures to manage hazards and seize opportunities to achieve their goals. ERM is an architecture for risk management that comprises five main elements: Continuity of operations, prevention and detection, response, mitigation, and recovery. It follows a structure based on identifying key

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Parallel Computing In Data Mining And Analysis
Data Science 101Data ScienceFeaturedTopics

Parallel Computing, also referred to as Parallel Processing, is a computing architecture that uses several processors to handle separate parts of an overall task. The architecture divides complex problems into small computations and distributes the workload between multiple processors working simultaneously. Parallel computing principles are employed in most supercomputers to

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What Is Data Redundancy?
Data Science 101Data ScienceTopics

Data redundancy means keeping data in two or more locations within a database or storage infrastructure. Data redundancy can occur either intentionally or accidentally within an organization. In case of data corruption or loss, the organization can continue operations or services if conscious redundancy is provided. On the other hand,

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