Jaganadh Gopinadhan jaganadhg

poetry env use $(which python)

poetry source add PyPi

poetry source add --priority=supplemental torch https://download.pytorch.org/whl/cu118

poetry add torch==2.0.1+cu118 --source torch

A large hotel reservation company wants to build the next generation hotel reservation and management system specifically tailored to high-end resorts and spas where guests can view and reserve specific rooms.

Users: Guests (hundreds), hotel staff (less than 20)

Requirements:

Registration can be made via web, mobile, phone call, or walk-in. Guests have the ability to either book a type of room (standard, deluxe, or suite) or choose a specific room to stay in by viewing pictures of each room and its location in the hotel.

English to Arabic Example-based Machine Translation System Assist. Prof. Suhad M. Kadhem, Yasir R. Nasir IJCCCE Vol.15, No.3, 2015 Paper Cited Man to Machine A tutorial on the art of Machine Translation”, 2010,http://www.slideshare.net/jaganadhg/a-tutorialon-machine-translation
OpenOffice.org Spell Checkr - http://www.openoffice.org/marketing/conference/foss.in_project_day.html
Foundation of the Computer Assisted Translation Act - The Online https://www.yumpu.com/en/document/read/43284606/foundation-of-the-computer-assisted-translation-act-the-online- -https://www.tojned.net/journals/tojned/articles/v03i04/v03i04-06.pdf Paper Cited Machine A tutorial on the art of Machine Translation
Towards Data Mart Building from Social Network for Opinion Analysis (Intelligent Data Engineering and Automated Learning -- IDEAL 2014:)

Codex Assists (Count)	Minimum Number of Problems Attempted	Maximum Number of Problems Attempted	Time Taken to Complete (Minimum)	Time Taken to Complete (Maximum)	Count of Participants
0	5	5	71	81	5
1	5	5	81	89	3
2	5	5	48	86	4
3	5	5	37	37	1
4	5	5	36	87	7
5	5	5	53	86	3
6	5	5	50	83	5
7	5	5	44	90	5
8	5	5	24	87	9

======================= ====================================== ====================================== ================================== ================================== ======================= Codex Assists (Count) Minimum Number of Problems Attempted Maximum Number of Problems Attempted Time Taken to Complete (Minimum) Time Taken to Complete (Maximum) Count of Participants
======================= ====================================== ====================================== ================================== ================================== ======================= 0 5 5 71 81 5
1 5 5 81 89 3
2

	SELECT DatabaseName, TableName, SUM(ReadCount) AS TotalReadCount
	FROM IDW_STATS_V.IDW_TABLE_USAGE_DETAILS
	GROUP BY DatabaseName, TableName
	ORDER BY TotalReadCount DESC;


	HELP COLUMN IDW_STATS_V.IDW_TABLE_USAGE_DETAILS.*;


	SELECT DatabaseName, TableName, SUM(AccessCount) AS TotalAccessCount

	sample = {
	"menu": {
	"id": "file",
	"value": "File",
	"popup": {
	"menuitem": [{
	"value": "New",
	"onclick": "CreateDoc()"
	}, {
	"value": "Open",

	import re

	sample_strm = "a%3b%2c:4d:5"

	def split_sort_smart(input_str):
	base_list = re.split(r'(\w+%\d+\|\w+:\d+)',input_str)

	split_pattern = '\|'.join(map(re.escape,['%',':']))

	base_list = [l for l in base_list if len(l) > 0]

	import re

	sample_str = "a%3,b%2,c:4,d:5"

	def spit_sort(inp_str, delims = ['%',':']):
	base_list = inp_str.split(",")

	split_pattern = '\|'.join(map(re.escape,delims))

	print(split_pattern)