{"id":"https://openalex.org/W4200554351","doi":"https://doi.org/10.1201/9781003185635","title":"Deep Learning","display_name":"Deep Learning","publication_year":2021,"publication_date":"2021-12-10","ids":{"openalex":"https://openalex.org/W4200554351","doi":"https://doi.org/10.1201/9781003185635"},"language":"en","primary_location":{"id":"doi:10.1201/9781003185635","doi":"https://doi.org/10.1201/9781003185635","is_oa":false,"landing_page_url":"https://doi.org/10.1201/9781003185635","pdf_url":null,"source":{"id":"https://openalex.org/S4306467597","display_name":"Chapman & Hall/CRC eBooks","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/P4310320449","host_organization_name":"Informa","host_organization_lineage":["https://openalex.org/P4310320449"],"host_organization_lineage_names":["Informa"],"type":"ebook platform"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":null,"raw_type":"monograph"},"volume":null,"type":"book","is_traditional":true,"indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5088256645","display_name":"Shriram K. Vasudevan","orcid":"https://orcid.org/0000-0002-4619-0079","observed_orcids":["https://orcid.org/0000-0002-4619-0079"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shriram K. Vasudevan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031398742","display_name":"Sini Raj Pulari","orcid":"https://orcid.org/0000-0001-6591-1655","observed_orcids":["https://orcid.org/0000-0001-6591-1655"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sini Raj Pulari","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5052104910","display_name":"Subashri Vasudevan","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Subashri Vasudevan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.2497,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.51028037,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":88,"max":95},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.5067999958992004,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.5067999958992004,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T13904","display_name":"Artificial Intelligence Applications","score":0.31369999051094055,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.11100000143051147,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/deep-learning","display_name":"deep learning","score":0.9990000128746033},{"id":"https://openalex.org/keywords/machine-learning","display_name":"machine learning","score":0.9200000166893005},{"id":"https://openalex.org/keywords/neural-network","display_name":"artificial neural networks","score":1.0},{"id":"https://openalex.org/keywords/convolutional-neural-networks","display_name":"convolutional neural networks","score":0.996999979019165},{"id":"https://openalex.org/keywords/recurrent-neural-networks","display_name":"recurrent neural networks","score":0.9990000128746033},{"id":"https://openalex.org/keywords/lstm","display_name":"LSTM","score":0.6830000281333923},{"id":"https://openalex.org/keywords/interview-questions","display_name":"interview questions","score":0.49799999594688416}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.39261379837989807},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.36133724451065063}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1201/9781003185635","doi":"https://doi.org/10.1201/9781003185635","is_oa":false,"landing_page_url":"https://doi.org/10.1201/9781003185635","pdf_url":null,"source":{"id":"https://openalex.org/S4306467597","display_name":"Chapman & Hall/CRC eBooks","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/P4310320449","host_organization_name":"Informa","host_organization_lineage":["https://openalex.org/P4310320449"],"host_organization_lineage_names":["Informa"],"type":"ebook platform"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":null,"raw_type":"monograph"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4386423592","https://openalex.org/W4414158132","https://openalex.org/W7211976566","https://openalex.org/W3112389553","https://openalex.org/W3009054233","https://openalex.org/W4250691089","https://openalex.org/W4200368665","https://openalex.org/W4285129539","https://openalex.org/W2985137303","https://openalex.org/W4414199505"],"abstract_inverted_index":{"Deep":[0,9],"Learning:":[1],"A":[2],"Comprehensive":[3],"Guide":[4],"provides":[5],"comprehensive":[6],"coverage":[7],"of":[8,58,66,69,78,120,173,205,208],"Learning":[10,14],"(DL)":[11],"and":[12,18,30,46,52,61,73,82,90,93,123,159,168,211],"Machine":[13],"(ML)":[15],"concepts.":[16],"DL":[17,105],"ML":[19,51,102],"are":[20],"the":[21,41,56,64,76,79,87,98,114,129,154,166,178,184],"most":[22],"sought-after":[23],"domains,":[24],"requiring":[25],"a":[26,118,134,141,144,171,194],"deep":[27,214],"understanding":[28,180],"\u2013":[29],"this":[31,150,218],"book":[32,39,151,199,219],"gives":[33],"no":[34],"less":[35],"than":[36],"that.":[37],"This":[38,198],"enables":[40],"reader":[42,130],"to":[43,104,131,176,183],"build":[44],"innovative":[45],"useful":[47],"applications":[48],"based":[49],"on":[50],"DL.":[53],"Starting":[54],"with":[55,143,165,170],"basics":[57],"neural":[59],"networks,":[60],"continuing":[62],"through":[63],"architecture":[65],"various":[67],"types":[68],"CNNs,":[70],"RNNs,":[71],"LSTM,":[72],"more":[74],"till":[75],"end":[77],"book,":[80],"each":[81],"every":[83],"topic":[84],"is":[85,193,200],"given":[86],"utmost":[88],"care":[89],"shaped":[91],"professionally":[92],"comprehensively.":[94],"Key":[95],"Features":[96],"Includes":[97,117,181],"smooth":[99],"transition":[100],"from":[101,149],"concepts":[103,106],"Line-by-line":[107],"explanations":[108],"have":[109],"been":[110],"provided":[111],"for":[112,196],"all":[113],"coding-based":[115],"examples":[116,122],"lot":[119],"real-time":[121],"interview":[124],"questions":[125,175],"that":[126,188],"will":[127,216],"prepare":[128],"take":[132],"up":[133],"job":[135],"in":[136,213],"ML/DL":[137],"right":[138],"away":[139],"Even":[140],"person":[142],"non-computer-science":[145],"background":[146],"can":[147],"benefit":[148],"by":[152],"following":[153],"theory,":[155],"examples,":[156],"case":[157],"studies,":[158],"code":[160],"snippets":[161],"Every":[162],"chapter":[163],"starts":[164],"objective":[167],"ends":[169],"set":[172],"quiz":[174],"test":[177],"reader\u2019s":[179],"references":[182],"related":[185],"YouTube":[186],"videos":[187],"provide":[189],"additional":[190],"guidance":[191],"AI":[192],"domain":[195],"everyone.":[197],"targeted":[201],"toward":[202],"everyone":[203],"irrespective":[204],"their":[206],"field":[207],"specialization.":[209],"Graduates":[210],"researchers":[212],"learning":[215],"find":[217],"useful.":[220]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1}],"updated_date":"2026-10-08T09:06:37.294493","created_date":"2021-12-31T00:00:00"}
