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Bihar Police Subordinate Services Commission (BPSSC) Bill was passed in Bihar State Assembly on 31 March 2016. The Government created the commission in order to handle the recruitment of subordinate staff of only those departments where the recruits covered are required to abide by certain physical fitness norms and also have to wear prescribed uniforms.
The Bihar Public Service Commission initially began its functioning for the State of Bihar with its headquarters at Ranchi. The State Government decided to shift the headquarters of the Commission from Ranchi to Patna and it was finally shifted to Patna on 1 March 1951. The first Chairman of the Bihar Public Service Commission was Shri ...
Database normalization is the process of structuring a relational database in accordance with a series of so-called normal forms in order to reduce data redundancy and improve data integrity. It was first proposed by British computer scientist Edgar F. Codd as part of his relational model .
In the simplest cases, normalization of ratings means adjusting values measured on different scales to a notionally common scale, often prior to averaging. In more complicated cases, normalization may refer to more sophisticated adjustments where the intention is to bring the entire probability distributions of adjusted values into alignment.
English: Dolch sight words from Pre-primary through 3rd Grade levels along with their phonetic Hindi counterparts. This is very useful for teaching correct pronounciation of essential english words to anyone familiar with the Hindi / devnagri script. Parents who don't know english can use this to teach the english words to their kids.
Second normal form (2NF), in database normalization, is a normal form. A relation is in the second normal form if it fulfills the following two requirements: It is in first normal form. It does not have any non-prime attribute that is functionally dependent on any proper subset of any candidate key of the relation (i.e. it lacks partial ...
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In machine learning, a key challenge is enabling models to accurately predict outcomes on unseen data, not just on familiar training data.Regularization is crucial for addressing overfitting—where a model memorizes training data details but can't generalize to new data.