
{"id":33989,"date":"2024-06-15T15:41:21","date_gmt":"2024-06-15T15:41:21","guid":{"rendered":"https:\/\/express24.ir\/d\/product\/%da%a9%d8%aa%d8%a7%d8%a8-%d8%b9%d9%84%d9%88%d9%85-%d9%be%db%8c%d8%b4%d8%b1%d9%81%d8%aa%d9%87-%d8%af%d8%a7%d8%af%d9%87-%d9%87%d8%a7-%d9%88-%d8%aa%d8%ac%d8%b2%db%8c%d9%87-%d9%88-%d8%aa%d8%ad%d9%84%db%8c\/"},"modified":"2024-06-15T12:12:28","modified_gmt":"2024-06-15T12:12:28","slug":"%da%a9%d8%aa%d8%a7%d8%a8-%d8%b9%d9%84%d9%88%d9%85-%d9%be%db%8c%d8%b4%d8%b1%d9%81%d8%aa%d9%87-%d8%af%d8%a7%d8%af%d9%87-%d9%87%d8%a7-%d9%88-%d8%aa%d8%ac%d8%b2%db%8c%d9%87-%d9%88-%d8%aa%d8%ad%d9%84%db%8c","status":"publish","type":"product","link":"https:\/\/express24.ir\/d\/product\/%da%a9%d8%aa%d8%a7%d8%a8-%d8%b9%d9%84%d9%88%d9%85-%d9%be%db%8c%d8%b4%d8%b1%d9%81%d8%aa%d9%87-%d8%af%d8%a7%d8%af%d9%87-%d9%87%d8%a7-%d9%88-%d8%aa%d8%ac%d8%b2%db%8c%d9%87-%d9%88-%d8%aa%d8%ad%d9%84%db%8c\/","title":{"rendered":"\u06a9\u062a\u0627\u0628 \u0639\u0644\u0648\u0645 \u067e\u06cc\u0634\u0631\u0641\u062a\u0647 \u062f\u0627\u062f\u0647 \u0647\u0627 \u0648 \u062a\u062c\u0632\u06cc\u0647 \u0648 \u062a\u062d\u0644\u06cc\u0644 \u0628\u0627 \u067e\u0627\u06cc\u062a\u0648\u0646"},"content":{"rendered":"<p>&nbsp;<\/p>\n<div style=\"text-align: center;\"><img decoding=\"async\" title=\"\u062f\u0627\u0646\u0644\u0648\u062f \u06a9\u062a\u0627\u0628 Advanced Data Science and Analytics with Python (Chapman &amp; Hall\/CRC Data Mining and Knowledge Discovery Series)\" src=\"https:\/\/express24.ir\/d\/wp-content\/uploads\/2024\/06\/9780429446610.jpg\" alt=\"\u062f\u0627\u0646\u0644\u0648\u062f \u06a9\u062a\u0627\u0628 Advanced Data Science and Analytics with Python (Chapman &amp; Hall\/CRC Data Mining and Knowledge Discovery Series)\" \/><\/div>\n<table class=\"table table-striped table-hover\">\n<tbody>\n<tr>\n<td>\n<h3>\u0639\u0646\u0648\u0627\u0646 \u06a9\u062a\u0627\u0628 \u0628\u0647 \u0627\u0646\u06af\u0644\u06cc\u0633\u06cc:<\/h3>\n<\/td>\n<td>\n<h3>Advanced Data Science and Analytics with Python (Chapman &amp; Hall\/CRC Data Mining and Knowledge Discovery Series)<\/h3>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<table class=\"table table-striped table-hover\">\n<tbody>\n<tr>\n<td>\u0633\u0627\u0644 \u0627\u0646\u062a\u0634\u0627\u0631: 2020\u00a0\u00a0|\u00a0\u00a0420 \u0635\u0641\u062d\u0647\u00a0\u00a0|\u00a0\u00a0\u062d\u062c\u0645 \u0641\u0627\u06cc\u0644: 22 \u0645\u06af\u0627\u0628\u0627\u06cc\u062a\u00a0\u00a0|\u00a0\u00a0\u0632\u0628\u0627\u0646: \u0627\u0646\u06af\u0644\u06cc\u0633\u06cc<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<table class=\"table table-striped table-hover\">\n<tbody>\n<tr>\n<td>\u0646\u0648\u06cc\u0633\u0646\u062f\u0647<\/td>\n<td>Jesus Rogel-Salazar<\/td>\n<\/tr>\n<tr>\n<td>\u0646\u0627\u0634\u0631<\/td>\n<td>CRC Press<\/td>\n<\/tr>\n<tr>\n<td>ISBN10:<\/td>\n<td>0429446616<\/td>\n<\/tr>\n<tr>\n<td>ISBN13:<\/td>\n<td>9780429446610<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<h2>\u062a\u0648\u0636\u06cc\u062d\u0627\u062a \u06a9\u062a\u0627\u0628<\/h2>\n<div style=\"direction: ltr;\">\n<p>Advanced Data Science and Analytics with Python enables data scientists to continue developing their skills and apply them in business as well as academic settings. The subjects discussed in this book are complementary and a follow-up to the topics discussed in Data Science and Analytics with Python. The aim is to cover important advanced areas in data science using tools developed in Python such as SciKit-learn, Pandas, Numpy, Beautiful Soup, NLTK, NetworkX and others. The model development is supported by the use of frameworks such as Keras, TensorFlow and Core ML, as well as Swift for the development of iOS and MacOS applications.<\/p>\n<p>Features:<\/p>\n<p>Targets readers with a background in programming, who are interested in the tools used in data analytics and data science<br \/>\nUses Python throughout<br \/>\nPresents tools, alongside solved examples, with steps that the reader can easily reproduce and adapt to their needs<br \/>\nFocuses on the practical use of the tools rather than on lengthy explanations<br \/>\nProvides the reader with the opportunity to use the book whenever needed rather than following a sequential path<\/p>\n<p>The book can be read independently from the previous volume and each of the chapters in this volume is sufficiently independent from the others, providing flexibility for the reader. Each of the topics addressed in the book tackles the data science workflow from a practical perspective, concentrating on the process and results obtained. The implementation and deployment of trained models are central to the book.<\/p>\n<p>Time series analysis, natural language processing, topic modelling, social network analysis, neural networks and deep learning are comprehensively covered. The book discusses the need to develop data products and addresses the subject of bringing models to their intended audiences \u2013 in this case, literally to the users\u2019 fingertips in the form of an iPhone app.<\/p>\n<p>About the Author<\/p>\n<p>Dr. Jes\u00fas Rogel-Salazar is a lead data scientist in the field, working for companies such as Tympa Health Technologies, Barclays, AKQA, IBM Data Science Studio and Dow Jones. He is a visiting researcher at the Department of Physics at Imperial College London, UK and a member of the School of Physics, Astronomy and Mathematics at the University of Hertfordshire, UK.<\/p>\n<\/div>\n<h2>\u062a\u0648\u0636\u06cc\u062d\u0627\u062a \u06a9\u062a\u0627\u0628 \u0628\u0647 \u0641\u0627\u0631\u0633\u06cc (\u062a\u0631\u062c\u0645\u0647 \u0645\u0627\u0634\u06cc\u0646\u06cc)<\/h2>\n<p>\u0639\u0644\u0648\u0645 \u0648 \u062a\u062c\u0632\u06cc\u0647 \u0648 \u062a\u062d\u0644\u06cc\u0644 \u062f\u0627\u062f\u0647 \u0647\u0627\u06cc \u067e\u06cc\u0634\u0631\u0641\u062a\u0647 \u0628\u0627 \u067e\u0627\u06cc\u062a\u0648\u0646 \u060c \u062f\u0627\u0646\u0634\u0645\u0646\u062f\u0627\u0646 \u062f\u0627\u062f\u0647 \u0631\u0627 \u0642\u0627\u062f\u0631 \u0645\u06cc \u0633\u0627\u0632\u062f \u062a\u0627 \u0645\u0647\u0627\u0631\u062a \u0647\u0627\u06cc \u062e\u0648\u062f \u0631\u0627 \u0627\u062f\u0627\u0645\u0647 \u062f\u0627\u062f\u0647 \u0648 \u0622\u0646\u0647\u0627 \u0631\u0627 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\u0634\u0648\u062f.<\/p>\n<p>\u0627\u0645\u06a9\u0627\u0646\u0627\u062a:<\/p>\n<p>\u062e\u0648\u0627\u0646\u0646\u062f\u06af\u0627\u0646 \u0631\u0627 \u0628\u0627 \u0633\u0627\u0628\u0642\u0647 \u0628\u0631\u0646\u0627\u0645\u0647 \u0646\u0648\u06cc\u0633\u06cc \u060c \u06a9\u0647 \u0628\u0647 \u0627\u0628\u0632\u0627\u0631\u0647\u0627\u06cc \u0645\u0648\u0631\u062f \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u062f\u0631 \u062a\u062c\u0632\u06cc\u0647 \u0648 \u062a\u062d\u0644\u06cc\u0644 \u062f\u0627\u062f\u0647 \u0647\u0627 \u0648 \u0639\u0644\u0648\u0645 \u062f\u0627\u062f\u0647 \u0639\u0644\u0627\u0642\u0647 \u0645\u0646\u062f \u0647\u0633\u062a\u0646\u062f \u060c \u0647\u062f\u0641 \u0642\u0631\u0627\u0631 \u0645\u06cc \u062f\u0647\u062f<br \/>\n\u062f\u0631 \u0633\u0631\u0627\u0633\u0631 \u0627\u0632 \u067e\u0627\u06cc\u062a\u0648\u0646 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0645\u06cc \u06a9\u0646\u062f<br \/>\n\u0627\u0628\u0632\u0627\u0631\u0647\u0627\u06cc\u06cc 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\u0628\u0631\u0627\u06cc \u06a9\u062a\u0627\u0628 \u0645\u0647\u0645 \u0627\u0633\u062a.<\/p>\n<p>\u062a\u062c\u0632\u06cc\u0647 \u0648 \u062a\u062d\u0644\u06cc\u0644 \u0633\u0631\u06cc \u0632\u0645\u0627\u0646\u06cc \u060c \u067e\u0631\u062f\u0627\u0632\u0634 \u0632\u0628\u0627\u0646 \u0637\u0628\u06cc\u0639\u06cc \u060c \u0645\u062f\u0644 \u0633\u0627\u0632\u06cc \u0645\u0648\u0636\u0648\u0639 \u060c \u062a\u062c\u0632\u06cc\u0647 \u0648 \u062a\u062d\u0644\u06cc\u0644 \u0634\u0628\u06a9\u0647 \u0647\u0627\u06cc \u0627\u062c\u062a\u0645\u0627\u0639\u06cc \u060c \u0634\u0628\u06a9\u0647 \u0647\u0627\u06cc \u0639\u0635\u0628\u06cc \u0648 \u06cc\u0627\u062f\u06af\u06cc\u0631\u06cc \u0639\u0645\u06cc\u0642 \u0628\u0647 \u0637\u0648\u0631 \u062c\u0627\u0645\u0639 \u062a\u062d\u062a \u067e\u0648\u0634\u0634 \u0642\u0631\u0627\u0631 \u0645\u06cc \u06af\u06cc\u0631\u0646\u062f.\u0627\u06cc\u0646 \u06a9\u062a\u0627\u0628 \u062f\u0631 \u0645\u0648\u0631\u062f \u0646\u06cc\u0627\u0632 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\u062f\u0627\u0646\u0634\u0645\u0646\u062f \u062f\u0627\u062f\u0647 \u0627\u0635\u0644\u06cc \u062f\u0631 \u0627\u06cc\u0646 \u0632\u0645\u06cc\u0646\u0647 \u0627\u0633\u062a \u0648 \u0628\u0631\u0627\u06cc \u0634\u0631\u06a9\u062a \u0647\u0627\u06cc\u06cc \u0645\u0627\u0646\u0646\u062f Tympa Health Technologies \u060c Barclays \u060c AKQA \u060c IBM Data Science Studio \u0648 \u062f\u0627\u0648 \u062c\u0648\u0646\u0632 \u06a9\u0627\u0631 \u0645\u06cc \u06a9\u0646\u062f.\u0648\u06cc \u06cc\u06a9 \u0645\u062d\u0642\u0642 \u0628\u0627\u0632\u062f\u06cc\u062f \u06a9\u0646\u0646\u062f\u0647 \u062f\u0631 \u06af\u0631\u0648\u0647 \u0641\u06cc\u0632\u06cc\u06a9 \u06a9\u0627\u0644\u062c \u0627\u0645\u067e\u0631\u06cc\u0627\u0644 \u0644\u0646\u062f\u0646 \u060c \u0627\u0646\u06af\u0644\u06cc\u0633 \u0648 \u0639\u0636\u0648 \u062f\u0627\u0646\u0634\u06a9\u062f\u0647 \u0641\u06cc\u0632\u06cc\u06a9 \u060c \u0646\u062c\u0648\u0645 \u0648 \u0631\u06cc\u0627\u0636\u06cc\u0627\u062a \u062f\u0631 \u062f\u0627\u0646\u0634\u06af\u0627\u0647 \u0647\u0631\u062a\u0641\u0648\u0631\u062f\u0634\u0627\u06cc\u0631 \u060c \u0627\u0646\u06af\u0644\u0633\u062a\u0627\u0646 \u0627\u0633\u062a.<br \/>\n<br \/>\r\n<table class=\"table table-bordered\">\r\n\t\r\n\t\t<tr>\r\n\t\t<td>\r\n\t\t\t\r\n\u062a\u0648\u062c\u0647 \u06a9\u0646\u06cc\u062f \u06a9\u0647 \u0627\u06cc\u0646 \u0645\u062d\u0635\u0648\u0644 \u0628\u0647 \u0635\u0648\u0631\u062a \u0641\u0627\u06cc\u0644 \u062f\u0627\u0646\u0644\u0648\u062f\u06cc \u0627\u0633\u062a \u0648 \u0646\u0647 \u06a9\u062a\u0627\u0628 \u06a9\u0627\u063a\u0630\u06cc.\r\n\r\n\t\t<\/td>\r\n\t<\/tr>\r\n\r\n\t\t<tr>\r\n\t\t<td>\r\n\t\t\t\r\n\u0628\u0647 \u0647\u0646\u06af\u0627\u0645 \u062e\u0631\u06cc\u062f \u0628\u0647 \u0632\u0628\u0627\u0646 \u062f\u0631\u062c \u0634\u062f\u0647 \u0628\u0631\u0627\u06cc \u06a9\u062a\u0627\u0628 \u062d\u062a\u0645\u0627 \u062a\u0648\u062c\u0647 \u06a9\u0646\u06cc\u062f. \u0628\u0647 \u0635\u0648\u0631\u062a \u0645\u0639\u0645\u0648\u0644 \u062f\u0631 \u0627\u06a9\u062b\u0631 \u0645\u0648\u0627\u0631\u062f \u0632\u0628\u0627\u0646 \u06a9\u062a\u0627\u0628 \u0641\u0627\u0631\u0633\u06cc \u0646\u06cc\u0633\u062a.\r\n\r\n\t\t<\/td>\r\n\t<\/tr>\t\r\n\r\n\t\t\t<tr>\r\n\t\t<td>\r\n\t\t\t\r\n\u062f\u0631 \u0635\u0648\u0631\u062a \u0647\u0631\u06af\u0648\u0646\u0647 \u0645\u0634\u06a9\u0644 \u062f\u0631 \u062f\u0631\u06cc\u0627\u0641\u062a \u06a9\u062a\u0627\u0628 \u0628\u0647 \u0634\u0645\u0627\u0631\u0647 09395106248 \u067e\u06cc\u0627\u0645\u06a9 \u062f\u0647\u06cc\u062f. \r\n\t\t<\/td>\r\n\t<\/tr>\t\r\n\t\r\n\t\t\t<tr>\r\n\t\t<td>\r\n\t\t\t\r\n\u062f\u0631\u062c \u0634\u0645\u0627\u0631\u0647 \u0645\u0648\u0628\u0627\u06cc\u0644 \u0628\u0631\u0627\u06cc \u0633\u0641\u0627\u0631\u0634 \u0636\u0631\u0648\u0631\u06cc \u0646\u06cc\u0633\u062a \u0648\u0644\u06cc \u062a\u0631\u062c\u06cc\u062d \u0622\u0646 \u0627\u0633\u062a \u062f\u0631\u062c \u06af\u0631\u062f\u062f \u062a\u0627 \u062f\u0631 \u0635\u0648\u0631\u062a \u0628\u0631\u0648\u0632 \u0645\u0634\u06a9\u0644 \u0627\u0648\u0644\u06cc\u0646 \u0631\u0627\u0647 \u0627\u0631\u062a\u0628\u0627\u0637\u06cc \u0645\u0627 \u0628\u0627 \u0634\u0645\u0627 \u0628\u0627\u0634\u062f.\r\n\t\t<\/td>\r\n\t<\/tr>\r\n\t\r\n\t<tr>\r\n\t\t<td>\r\n\t\t\t\r\n\t\t\t\u0686\u0646\u0627\u0646\u0686\u0647 \u062f\u0631 \u062f\u0631\u06cc\u0627\u0641\u062a \u0645\u062d\u0635\u0648\u0644 \u0628\u0647 \u0647\u0631 \u062f\u0644\u06cc\u0644\u06cc \u0628\u0627 \u0645\u0634\u06a9\u0644 \u0631\u0648\u0628\u0631\u0648 \u0634\u062f\u06cc\u062f \u0648 \u0645\u0637\u0645\u0626\u0646 \u0627\u0632 \u067e\u0631\u062f\u0627\u062e\u062a \u0645\u0648\u0641\u0642 \u0648\u062c\u0647 \u0647\u0633\u062a\u06cc\u062f \u0628\u0647 \u0634\u0645\u0627\u0631\u0647 \u062a\u0645\u0627\u0633 \u0632\u06cc\u0631 \u0646\u0627\u0645\u060c \u0646\u0627\u0645 \u062e\u0627\u0646\u0648\u0627\u062f\u06af\u06cc \u0648 \u0646\u0627\u0645 \u0645\u062d\u0635\u0648\u0644 \u0631\u0627 \u067e\u06cc\u0627\u0645\u06a9 \u0628\u0632\u0646\u06cc\u062f \u062a\u0627 \u0644\u06cc\u0646\u06a9 \u0645\u062d\u0635\u0648\u0644 \u0633\u0631\u06cc\u0639\u0627 \u0628\u0631\u0627\u06cc \u0634\u0645\u0627 \u0627\u0631\u0633\u0627\u0644 \u06af\u0631\u062f\u062f.\r\n\t\t\t<br \/><br \/>\r\n\t\t\t\u0634\u0645\u0627\u0631\u0647 \u062a\u0645\u0627\u0633: 09395106248 \r\n\r\n\t\t<\/td>\r\n\t<\/tr>\r\n\t\r\n<\/table>\r\n<br \/>\r\n\r\n<\/p>\n","protected":false},"excerpt":{"rendered":"<p>&nbsp; \u0639\u0646\u0648\u0627\u0646 \u06a9\u062a\u0627\u0628 \u0628\u0647 \u0627\u0646\u06af\u0644\u06cc\u0633\u06cc: Advanced Data Science and Analytics with Python (Chapman &amp; Hall\/CRC Data Mining and Knowledge Discovery 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