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Designing an ML system involves balancing trade-offs between accuracy, latency, cost, and maintainability, while ensuring system scalability and reliability. The discipline overlaps with MLOps, a set of practices that unifies machine learning development and operations to ensure smooth deployment and lifecycle management of ML systems.
The company was launched in 2014. [1] Its name, Vedantu, is derived from the Sanskrit words Veda (knowledge) and Tantu (network). [2] The organization is run by IIT alumni Vamsi Krishna (co-founder and CEO), Pulkit Jain (co-founder and head of product), Saurabh Saxena (co-founder) and Anand Prakash (co-founder and head of academics).
The start-up was part of the first batch of GSF Accelerator in 2012, [10] and it later secured $500,000 from early-stage investor Prime Ventures. [11] The Bangalore and California -based company raised $4.5 million in a Series A [ 12 ] round funding led by DHI Group Inc. with participation from Prime Ventures and Beenext in February 2017. [ 4 ]
A child's hand location and movement being detected by a gesture recognition algorithm. Gesture recognition is an area of research and development in computer science and language technology concerned with the recognition and interpretation of human gestures.
Software engineering is a field within computer science focused on designing, developing, testing, and maintaining of software applications.It involves applying engineering principles and computer programming expertise to develop software systems that meet user needs.
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Cem Kaner, who coined the term in 1984, [26] defines exploratory testing as "a style of software testing that emphasizes the personal freedom and responsibility of the individual tester to continually optimize the quality of his/her work by treating test-related learning, test design, test execution, and test result interpretation as mutually ...
The most recent book on speech recognition is Automatic Speech Recognition: A Deep Learning Approach (Publisher: Springer) written by Microsoft researchers D. Yu and L. Deng and published near the end of 2014, with highly mathematically oriented technical detail on how deep learning methods are derived and implemented in modern speech ...
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