Ngesikhathi esidumile lapho ukusebenza kwe-supply chain ivimbele ngqo imiphumela yebhizinisi, ukusetshenziswa kwe-Perpetual Inventory (PI) Optimization Model kuyinto isitifiketi sokusebenza kwe-problem-solving kanye ne-technical excellence. Nge-leading of Shiva Kumar Ramavath, a professional e-Data Science kanye ne-Artificial Intelligence, le nophuhliso esidumile lihlanganisa izinzuzo ezintsha zokulawula i-inventory kanye ne-supply chain optimization, ukubonisa amandla wokuguqulwa kwe-AI ekuphenduleni izinzuzo ezinzima zebhizinisi. I-impact project ye-120 million US$ lithunyelwe njenge-challenge ebalulekile ekuthuthukiseni isikhunta se-supply chain, ekuthuthukiseni isilinganiso esiyingqayizivele phakathi kokuvimbela i-stock-outs nokuvimbela izimo ze-overstock eziningana nezindawo ezininzi zoshishino. Nge-responsibility ye-end-to-end project delivery, i-Shiva Kumar Ramavath wathatha umsebenzi enhle yokwenza nokuthuthukiswa kwe-machine-learning-based classification model kanye nokupholisa ukuxhumana okuzenzakalelayo phakathi kwamakhemikhali zamabhizinisi nama-stakeholders. I-complexity ye-challenge lithunyelwe ngempumelelo eminingi, kuhlanganise idatha yokuthengisa okuhlaziywa, izimo zok Njengomakhi yokuqala we-solution, i-Shiva Kumar Ramavath yasungula izindlela ezintsha zokuhlanza zokuhlanza ukuthi akufanele kuphela ama-performance targets kodwa kakhulu. I-Project iye yenza ukunciphisa i-15% ye-out-of-stock rates kanye nokukhuthaza i-$120 million yentengiso yentengiso – umphumela ephakeme kwebhizinisi ebizwa ngokuvamile nge-inventory management complexities kanye ne-demand volatility. Lo mphumela yakhelwe ku-foundation ye-analytics ephakeme, kuhlanganise ama-algorithms eyinhloko ye-machine learning okuyinto angakwazi ukuxazulula kanye nokuhlola amaningi ama-data ukuze zihlanganise izinga ezingenalutho zokuhlanza kanye nezinzuzo zokuh Ukukhiqizwa kwezobuchwepheshe zihlanganisa ubuchwepheshe we-Shiva ekuthuthukiseni izixazululo ze-AI. I-model architecture yenzelwe ngokucacileyo ukuhlangabezana ne-complexity ye-multi-store inventory management, okuhlanganise izici ezinzima ezifana nokushintshwa kwezidingo, ukuguqulwa kwe-seasonality, kanye ne-analysis ye-impact yokukhuthaza. I-robustness ye-solution yaziwa ngokuvumelana nezimo eziningana ze-market ne-store-specific patterns, ukuhlangabezana nokusebenza okuqhubekayo phakathi izindawo ezahlukene kanye nemikhiqizo amasethi. Umphumela we-Leadership wahluka ngaphezulu kwezimo zokufinyelelwa kwezimali. Nge-implementation yezinhlangano kanye nokuthuthukiswa kwamamodeli efanelekayo, le nkqubo yandisa izindleko zokufinyelela kwezimpahla kanye nokusetshenziswa kwezimpahla. Umthamo we-optimization ye-optimization yokufinyelela izindleko zokufinyelela kwezimpahla ezingenalutho kanye nokufinyelela izici zokufinyelela ezinhle zihlanganisa izindlela zokufinyelela zokufinyelela kwezimpahla ezivamile, uvumela izinga elisha lokuphelelwa kwezimali kanye nokuthuthukiswa kwezimali zokusebenza kwenethiwekhi zokupakisha. Mhlawumbe kakhulu kakhulu, lezi zithuthukiswa zitholakala ngenkathi zihlanganisa ukusebenza kwezimpahla zokufinyelela kwez Ukusebenza okungenani kanye nokuhlanganiswa okuhlobene nezinkqubo zebhizinisi ziye zibonisa ikhono we-Shiva ukukhuthaza ingxubevange phakathi kwezobuchwepheshe zokusebenza nezidingo zebhizinisi zokusebenza. Ukusebenzisana kwe-cross-functional, kuhlanganise ama-supply chain planners, ama-engineers, ne-business stakeholders, ivimbele ukuthi isixazululo uyihambisana nezidingo zebhizinisi kanye nokukhuthaza izinzuzo zebhizinisi zebhizinisi. Izinhlelo zokusebenza zokusebenza zokusebenza zihlanganisa ngokushesha futhi zihlanganisa nezidingo zebhizinisi ezintsha. Inqubo yokukhiqiza inkqubo yakhelwe ukucindezeleka kokushintshwa kokushintshwa nokuthuthukiswa kwamakhasimende. I-Shiva yasungulwa izinhlelo zokusebenza ephelele kanye nokubhekiselela ukuqinisekisa ukuthi abasebenzisi be-business angakwazi ukufinyelela ngokuvumelana nesistimu ekusebenziseni kwezimfuneko ezithile. Lokhu ukucindezeleka ku-usability kanye nokusetshenziswa kwe-praktikum kubalulekile ukufinyelela kwama-adoption ephezulu nokwandisa imiphumela yebhizinisi ye-solution. Umphumela wabhala umthamo we-AI yokuguqulwa kwezimfuneko ezivamile ze-supply chain, ukwamukela ukubuyekezwa ngenxa ye-approximation yayo yobuchwepheshe kanye nemiphumela yebhizinisi esikhulu. Umphumela we-Project uye kwenziwa kwama-benchmark ye-AI emkhakheni sokuphathwa komthwalo, okuvumela ukuthi ukwakhiwa okuphumelelayo kwezobuchwepheshe kanye ne-strategic thinking kunikeza imiphumela emangalisayo phakathi kwezinga lokusebenza eziningi. Umphumela we-Solution ukukhiqiza izinzuzo ezingenalayo zebhizinisi kanye nezimfuneko zokusebenza eminyakeni okwenza izinga ezintsha ze-AI amaphrojekthi e-industry. Ukuze u-Shiva Kumar Ramavath ngokufanayo, le nophuhliso lihlanganisa isikhokelo esikhulu emkhakheni wayo esiyingqayizivele. Ngokuzenza i-PhD yayo ku-AI, nge-Master's degree ku-Data Science kusuka e-University of North Texas, uShiva inikeza eminyakeni engaphezu kwama-experience ekuthuthukiseni izixazululo ze-AI ephezulu. I-expertise yayo iveza izindawo ezahlukene, kusuka ku-fraud detection kuya ku-recommendation systems, ngokuvamile ukunikela izixazululo ezivela ukuhlanganiswa kwe-technical excellence ne-business value. Ukulungiselela indlela yokuphumelela kwiprojekthi okuvumela indlela yokuphumelela kokuphumelela kokuphumelela kokuphumelela kokuphumelela kokuphumelela kokuphumelela kokuphumelela kokuphumelela kokuphumelela kokuphumelela kokuphumelela kokuphumelela kokuphumelela kokuphumelela kokuphumelela kokuphumelela kokuphumelela kokuphumelela kokuphumelela kokuphumelela kokuphumelela kokuphumelela kokuphumelela kokuphumelela kokuphumelela kokuphumelela kokuphumelela kokuphumelela kokuphumelela kokuphumelela kokuphumelela. Ukubonisa indlela efanelekayo yokukhiqizwa kwe-AI kunokufinyelela izinzuzo zebhizinisi ezinzima ngokuvumelana nomthelela i-value engapheliyo kubangaphakathi. Le nkqubo ivela indlela yokuqinisekisa izinzuzo zokusebenza kwe-supply chain optimization, okuvumela indlela yokukhishwa kwe-analytics ephakeme kanye ne-machine learning ukuze zibonele izinzuzo zokuthengisa ezisebenzayo. Njengoba indawo ye-AI isebenza ngokushesha, umsebenzi we-Shiva Kumar Ramavath inikeza njenge-model yokukhiqiza okusheshayo, okuvumela ukuhlanganiswa okuphakeme kwe-technical expertise, ukusebenza okuphakeme, kanye ne-strategic thinking ekukhuthaza umphumela we-project. I-Shiva Kumar Ramavath I-innovative leader ku-intelligent kanye ne-data science, i-Shiva Kumar Ramavath inikeza ukuxhaswa kwe-academic excellence ne-implementation esebenzayo emkhakheni eyenza ngokushesha ye-AI. Njengomongameli we-doctoral eyenza ku-artificial intelligence, ukuhlolwa kwayo lihlanganisa ukuxhaswa ama-limits eyenziwa kwezicelo ze-machine learning. Umhlahlandlela wakhe wokufundisa, kuhlanganise i-Master's in Data Science kusuka eYunivesithi yaseNorth Texas, uye wahlanganisa ukuxhaswa okuqhubekayo kwezobuchwepheshe ze-analytical kanye nezinhlelo ezintsha ze-AI. Phakathi nesikolo se-professional esidlulile eminyakeni, i-Shiva ibonise ikhono esizodwa yokuguqulwa kwezinkonzo ezizobuchwepheshe ezinzima ekusebenziseni izixazululo zebhizinisi. I-Portfolio yayo ibandakanya umsebenzi wokugqibela eminyakeni eziningi, kusukela ekuthuthukiseni izinhlelo zokusebenza zokuthintela ama-fraud kuya ekwenzeni izinjini ezintsha ze-recommendation. Isisombululo se-Shiva ibandakanya ukucindezeleka okuhlobene kwe-analytical ne-comprehensive understanding ye-business objectives, okuholela izixazululo ezizayo akuyona kuphela ubuchwepheshe okuhlobene kodwa futhi inikeza umphumela wokuthumela kwebhizinisi I-Expertise ye-Shiva ibonise ngaphandle kwezicelo zokusebenza zebhizinisi zebhizinisi ezivamile kwegama lokusebenza kwe-AI emkhakheni yebhizinisi. Ukusebenza kwayo kwebhizinisi lokusebenza, ikakhulukazi i-PI Optimization Model, ibonise ikhono wayo ukuxhumana nezimo zebhizinisi ezinzima ngokusebenzisa izixazululo ezintsha ze-AI. I-Intelligence ye-Intelligence ye-Intelligence ye-Intelligence ye-Intelligence ye-Intelligence ye-Intelligence ye-Intelligence. Lesi sihloko lithunyelwe njenge-release ngu-Echospire Media ngaphansi kwe-HackerNoon's Business Blogging Program. Funda kabanzi mayelana ne-program lapha. Lesi sihloko lithunyelwe njenge-release ye-Echospire Media ngaphansi kwe-HackerNoon's Business Blogging Program. Funda kabanzi mayelana ne-program . here Ngiya
