Search results
Results From The WOW.Com Content Network
The Eiffel class ANY contains features for shallow and deep copying and cloning of objects. All Eiffel classes inherit from ANY, so these features are available within all classes, and are applicable both to reference and expanded objects. The copy feature effects a shallow, field-by-field copy from one object to another. In this case no new ...
The re-construction of the Board of Intermediate and Secondary Education, Lahore has been done through the Punjab Boards of Intermediate and Secondary Education Act 1976 (lately amended by Punjab Ordinance No.XLVII). Currently, nine Boards are functioning in the Punjab province at division level.
The Board is autonomous in nature. The central forum is called Punjab Boards Committee of Chairmen (PBCC) and all the BISE's in Punjab take over the Chairmanship for one year in alphabetical order. Mr. Muhammad Adnan Khan is the current chairman of the Board. The Board was established in October, 1977.
The Board is headed by a full-time Chairman whose term lasts three years and who technically reports to the Secretary of School Education in the Government of Punjab.The current Education Secretary of the board is IAS Sh Harsant Singh sekhon who is sincerely committed to shape the education system of Punjab by his pioneering Initiatives like ...
Board Established City Website Refs Catholic Board of Education, Pakistan: 1961 Karachi [47] Lahore [48] [49] Diocesan board of education, Pakistan 1960 Islamabad, Rawalpindi [50] [51] Presbyterian Education Board Pakistan Lahore, Punjab
A primary school book published under Sarva Shiksha Abhiyan Punjab. Sarva Shiksha Abhiyan was started in 2000s by the government of India to provide free and compulsory education to the children from 6 to 14 years of age. [9] In August 2024, Punjab government announced that it is planning to start a new project called "Schools of happiness".
Pages in category "Education boards in Punjab, Pakistan" The following 9 pages are in this category, out of 9 total. This list may not reflect recent changes .
Deep models (CAP > two) are able to extract better features than shallow models and hence, extra layers help in learning the features effectively. Deep learning architectures can be constructed with a greedy layer-by-layer method. [11] Deep learning helps to disentangle these abstractions and pick out which features improve performance. [8]