Python	book	by	reema	thareja
                                          I'm	not	robot!
                                      Python	book	by	reema	thareja
  Python	book	by	reema	thareja	pdf.	Python	books	by	indian	authors.	Python	programming	book	by	reema	thareja	pdf	download.	Python	books	for	intermediate.	Python	programming	book	by	reema	thareja.	Python	order	book	analysis.	Python	book	for	beginners	indian	author.	
  Reema	Thareja,	Assistant	Professor,	Department	of	Computer	Science,	Shyama	Prasad	Mukherji	College,	University	of	Delhi	Reema	Thareja	is	Assistant	Professor	at	Department	of	Computer	Science,	Shyama	Prasad	Mukherji	College	for	Women,	University	of	Delhi.	She	has	completed	MCA	in	Software	Engineering,	MPhil	in	Computer	Science,	and
  PhD	in	the	area	of	improving	data	warehouse	quality.	She	has	around	12	years	of	teaching	experience	and	specializes	in	programming	languages,	operating	systems,	microprocessors,	DBMS,	multimedia,	and	web	technologies.	Dr	Thareja	has	published	several	research	papers	in	national	and	international	journals	of	repute.	She	has	done	projects	on
  quality	monitoring	of	ATM	networks	and	on	steganography	in	Centre	for	Development	of	Telematics	(CDoT)	and	Defence	Research	and	Development	Organisation	(DRDO),	respectively.	She	is	the	member	of	Computer	Society	of	India	(CSI).	She	has	also	authored	several	books	for	OUP,	India.	Features	Complete	coverage	of	the	Problem	Solving	and
  Python	Programming	syllabus	offered	by	Anna	University.	Simple	and	to-the-point	explanations	of	concepts	using	numerous	programming	examples	that	make	the	text	easy	to	understand.	Detailed	coverage	of	fundamental	constructs,	strings,	file	handling,	classes,	and	exception	handling	in	Python.	Notes	and	programming	tips	provided	to	emphasize
  on	the	important	concepts	and	help	readers	avoid	common	programming	errors.	Lab	exercises	and	illustrative	examples	explained	through	algorithms	and	flowcharts	to	help	readers	hone	their	logical	and	programming	abilities.	Case	studies	on	creating	calculator,	calendar,	and	hash	files,	compressing	strings	and	files,	image	processing,	shuffling	a
  deck	of	cards,	and	mail	merge	along	with	programs	are	interspersed	within	the	text.	Strong	chapter-end	pedagogy	including	plenty	of	objective-type	questions,	review	questions,	programming	and	debugging	exercises	to	facilitate	revision	and	practice	of	concepts	learnt.	2	solved	question	papers	and	2	solved	model	question	papers	included	to	help
  readers	prepare	for	the	university	examinations.	6	annexures	and	4	appendices	covering	differences	between	Python	2.x	and	3.x,	installing	Python,	debugging	and	testing,	Turtle	graphics,	plotting	graphs,	and	GUI	Programming	provided	to	supplement	the	text.	New	to	this	Edition	New	topics	as	required	by	the	syllabus	such	as	Python	interpreter	and
  interactive	mode,	Fruitful	functions,	function	composition,	mutability,	list	parameters,	list	as	arrays,	Boolean	values	and	operators	More	illustrative	examples	added	under	Algorithms,	Pseudocode,	and	Flowcharts	Elaboration	on	topics	such	as	modules,	packages,	command	line	arguments	(under	File	Handling)	Complete	solutions	for	previous	years'
  Anna	University	question	papers	of	Python	Programming	(Dec/	Jan	2017/18	and	Dec/	Jan	2018/19)	Online	Resources	For	Faculty	Chapter-wise	PPTs	Solutions	Manual	Chapters	on	Inheritance	and	Operator	Overloading	Additional	Material	For	Students	Lab	Exercises	Test	Generator	Projects	Solutions	to	Find	the	Output	and	Error	Exercises	Extra
  Reading	Material	Additional	Algorithms,	Pseudocodes,	and	Flowcharts	Skip	to	main	search	results	Page	2	Skip	to	main	search	results	Soft	cover.	Condition:	New.	The	book	Introduction	to	Python	Programming:	A	Practical	Approach	lays	out	a	path	for	readers	who	want	to	pursue	a	career	in	the	field	of	computer	software	development.	It	covers	the
  fundamentals	of	Python	programming	as	well	as	machine	learning	principles.	Students	will	benefit	from	the	examples	that	are	included	with	each	concept,	which	will	aid	them	in	understanding	the	concept.	This	book	provides	a	practical	understanding	of	Python	programming	using	numerous	programs	and	examples.	It	also	develops	problem-solving
  and	code-writing	abilities	for	the	readers.	This	book	covers	Python	fundamentals,	operators,	and	data	structures	such	as	strings,	lists,	dictionaries,	and	tuples.	It	also	contains	information	on	file	and	exception	handling.	The	implementation	of	a	machine	learning	model	has	also	been	included	in	this	book.	With	the	help	of	this	book,	students	and
  programmers	can	improve	their	programming	skills	as	well	as	their	ability	to	sprint	towards	a	rewarding	career.	Paperback.	Condition:	New.	Language:	English.	Brand	new	Book.	Discover	easy-to-follow	solutions	and	techniques	to	help	you	to	implement	applied	mathematical	concepts	such	as	probability,	calculus,	and	equations	using	Python's
  numeric	and	scientific	librariesKey	FeaturesCompute	complex	mathematical	problems	using	programming	logic	with	the	help	of	step-by-step	recipesLearn	how	to	utilize	Python's	libraries	for	computation,	mathematical	modeling,	and	statisticsDiscover	simple	yet	effective	techniques	for	solving	mathematical	equations	and	apply	them	in	real-world
  statisticsBook	DescriptionPython,	one	of	the	world's	most	popular	programming	languages,	has	a	number	of	powerful	packages	to	help	you	tackle	complex	mathematical	problems	in	a	simple	and	efficient	way.	These	core	capabilities	help	programmers	pave	the	way	for	building	exciting	applications	in	various	domains,	such	as	machine	learning	and
  data	science,	using	knowledge	in	the	computational	mathematics	domain.	The	book	teaches	you	how	to	solve	problems	faced	in	a	wide	variety	of	mathematical	fields,	including	calculus,	probability,	statistics	and	data	science,	graph	theory,	optimization,	and	geometry.	You'll	start	by	developing	core	skills	and	learning	about	packages	covered	in
  Python's	scientific	stack,	including	NumPy,	SciPy,	and	Matplotlib.	As	you	advance,	you'll	get	to	grips	with	more	advanced	topics	of	calculus,	probability,	and	networks	(graph	theory).	After	you	gain	a	solid	understanding	of	these	topics,	you'll	discover	Python's	applications	in	data	science	and	statistics,	forecasting,	geometry,	and	optimization.	The	final
  chapters	will	take	you	through	a	collection	of	miscellaneous	problems,	including	working	with	specific	data	formats	and	accelerating	code.	By	the	end	of	this	book,	you'll	have	an	arsenal	of	practical	coding	solutions	that	can	be	used	and	modified	to	solve	a	wide	range	of	practical	problems	in	computational	mathematics	and	data	science.What	you	will
  learnGet	familiar	with	basic	packages,	tools,	and	libraries	in	Python	for	solving	mathematical	problemsExplore	various	techniques	that	will	help	you	to	solve	computational	mathematical	problemsUnderstand	the	core	concepts	of	applied	mathematics	and	how	you	can	apply	them	in	computer	scienceDiscover	how	to	choose	the	most	suitable	package,
  tool,	or	technique	to	solve	a	certain	problemImplement	basic	mathematical	plotting,	change	plot	styles,	and	add	labels	to	the	plots	using	MatplotlibGet	to	grips	with	probability	theory	with	the	Bayesian	inference	and	Markov	Chain	Monte	Carlo	(MCMC)	methodsWho	this	book	is	forThis	book	is	for	professional	programmers	and	students	looking	to
  solve	mathematical	problems	computationally	using	Python.	Advanced	mathematics	knowledge	is	not	a	requirement,	but	a	basic	knowledge	of	mathematics	will	help	you	to	get	the	most	out	of	this	book.	The	book	assumes	familiarity	with	Python	concepts	of	data	structures.	Page	3	Enter	at	least	one	of	author,	title,	ISBN,	keyword,	or	publisher	to
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