標(biāo)題: Titlebook: Data Science Solutions with Python; Fast and Scalable Mo Tshepo Chris Nokeri Book 2022 Tshepo Chris Nokeri 2022 Big Data Analytics.Machine [打印本頁] 作者: 天真無邪 時(shí)間: 2025-3-21 17:52
書目名稱Data Science Solutions with Python影響因子(影響力)
書目名稱Data Science Solutions with Python影響因子(影響力)學(xué)科排名
書目名稱Data Science Solutions with Python網(wǎng)絡(luò)公開度
書目名稱Data Science Solutions with Python網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Data Science Solutions with Python被引頻次
書目名稱Data Science Solutions with Python被引頻次學(xué)科排名
書目名稱Data Science Solutions with Python年度引用
書目名稱Data Science Solutions with Python年度引用學(xué)科排名
書目名稱Data Science Solutions with Python讀者反饋
書目名稱Data Science Solutions with Python讀者反饋學(xué)科排名
作者: OGLE 時(shí)間: 2025-3-21 23:15
oduces DL and an artificial neural network known as the Multilayer Perceptron (MLP) classifier. A way of performing cluster analysis using the K-Means model is covered. Dimension reduction techniques such as Pr978-1-4842-7761-4978-1-4842-7762-1作者: Nonthreatening 時(shí)間: 2025-3-22 01:57
and scaling them.Bridges the gap between machine and deep lApply supervised and unsupervised learning to solve practical and real-world big data problems. This book teaches you how to engineer features, optimize hyperparameters, train and test models, develop pipelines, and automate the machine lea作者: 破譯密碼 時(shí)間: 2025-3-22 05:08
Leszek J. Chmielewski,Arkadiusz Or?owskiected, manipulated, and examined using resilient and fault-tolerant technologies. It discusses the Scikit-Learn, Spark MLlib, and XGBoost frameworks. It also covers a deep learning framework called Keras. It concludes by discussing effective ways of setting up and managing these frameworks.作者: B-cell 時(shí)間: 2025-3-22 09:45
Big Data, Machine Learning, and Deep Learning Frameworks,ected, manipulated, and examined using resilient and fault-tolerant technologies. It discusses the Scikit-Learn, Spark MLlib, and XGBoost frameworks. It also covers a deep learning framework called Keras. It concludes by discussing effective ways of setting up and managing these frameworks.作者: 姑姑在炫耀 時(shí)間: 2025-3-22 16:39 作者: 姑姑在炫耀 時(shí)間: 2025-3-22 19:25 作者: Control-Group 時(shí)間: 2025-3-22 22:28
http://image.papertrans.cn/d/image/263069.jpg作者: eczema 時(shí)間: 2025-3-23 04:13 作者: 小淡水魚 時(shí)間: 2025-3-23 06:10
https://doi.org/10.1007/978-3-031-00978-5This introductory chapter explains the ordinary least-squares method and executes it with the main Python frameworks (i.e., Scikit-Learn, Spark MLlib, and H2O). It begins by explaining the underlying concept behind the method.作者: 細(xì)絲 時(shí)間: 2025-3-23 11:19 作者: Initiative 時(shí)間: 2025-3-23 17:06 作者: 血友病 時(shí)間: 2025-3-23 18:55 作者: 里程碑 時(shí)間: 2025-3-23 23:57
Teruyo Wada,Masao Ikeda,Eiho UezatoThis chapter executes and assesses nonlinear neural networks to address binary classification using a diverse set of comprehensive Python frameworks (i.e., Scikit-Learn, Keras, and H2O).作者: incubus 時(shí)間: 2025-3-24 06:17 作者: Judicious 時(shí)間: 2025-3-24 09:31
https://doi.org/10.1007/978-1-4684-1605-3This chapter executes a simple dimension reducer (a principal component method) by implementing a diverse set of Python frameworks (Scikit-Learn, PySpark, and H2O). To begin, it clarifies how the method computes components.作者: Fantasy 時(shí)間: 2025-3-24 12:23 作者: AGGER 時(shí)間: 2025-3-24 17:02 作者: Endemic 時(shí)間: 2025-3-24 20:11 作者: interrogate 時(shí)間: 2025-3-25 01:53
Survival Analysis withPySpark and Lifelines,This chapter describes and executes several survival analysis methods using the main Python frameworks (i.e., Lifelines and PySpark). It begins by explaining the underlying concept behind the Cox Proportional Hazards model. It then introduces the accelerated failure time method.作者: 清真寺 時(shí)間: 2025-3-25 06:39
Nonlinear Modeling With Scikit-Learn, PySpark, and H2O,This chapter executes and appraises a nonlinear method for binary classification (called .) using a diverse set of comprehensive Python frameworks (i.e., Scikit-Learn, Spark MLlib, and H2O). To begin, it clarifies the underlying concept behind the sigmoid function.作者: 多產(chǎn)魚 時(shí)間: 2025-3-25 10:27 作者: Fulminate 時(shí)間: 2025-3-25 15:30
Neural Networks with Scikit-Learn, Keras, and H2O,This chapter executes and assesses nonlinear neural networks to address binary classification using a diverse set of comprehensive Python frameworks (i.e., Scikit-Learn, Keras, and H2O).作者: LIEN 時(shí)間: 2025-3-25 17:15
Cluster Analysis with Scikit-Learn, PySpark, and H2O,This chapter explains the . cluster method by implementing a diverse set of Python frameworks (i.e., Scikit-Learn, PySpark, and H2O). To begin, it clarifies how the method apportions values to clusters.作者: 條街道往前推 時(shí)間: 2025-3-25 21:14
Principal Component Analysis with Scikit-Learn, PySpark, and H2O,This chapter executes a simple dimension reducer (a principal component method) by implementing a diverse set of Python frameworks (Scikit-Learn, PySpark, and H2O). To begin, it clarifies how the method computes components.作者: interlude 時(shí)間: 2025-3-26 01:44 作者: Emmenagogue 時(shí)間: 2025-3-26 04:44
Leszek J. Chmielewski,Arkadiusz Or?owski(ML) and deep learning (DL) frameworks useful for building scalable applications. After reading this chapter, you will understand how big data is collected, manipulated, and examined using resilient and fault-tolerant technologies. It discusses the Scikit-Learn, Spark MLlib, and XGBoost frameworks. 作者: 抱負(fù) 時(shí)間: 2025-3-26 10:33 作者: fetter 時(shí)間: 2025-3-26 13:49
978-1-4842-7761-4Tshepo Chris Nokeri 2022作者: hypotension 時(shí)間: 2025-3-26 17:43
Big Data, Machine Learning, and Deep Learning Frameworks,(ML) and deep learning (DL) frameworks useful for building scalable applications. After reading this chapter, you will understand how big data is collected, manipulated, and examined using resilient and fault-tolerant technologies. It discusses the Scikit-Learn, Spark MLlib, and XGBoost frameworks. 作者: euphoria 時(shí)間: 2025-3-26 21:00
Die Diagnose der Schlafkrankheit,schen und mikromorphologischen Variabilit?t des Hauttumors mu? die Entscheidung für den Einsatz tiefer Temperaturen auf den jeweiligen Einzelfall abgestimmt werden. Da die Radikalit?t des Vorgehens histologisch nicht kontrolliert werden kann [4], erfordert die Kryotherapie des Basalioms eine besonde作者: 戲服 時(shí)間: 2025-3-27 02:16 作者: STIT 時(shí)間: 2025-3-27 06:33 作者: 彩色的蠟筆 時(shí)間: 2025-3-27 09:39 作者: Critical 時(shí)間: 2025-3-27 15:11
Archaean Crystalline Rocks of the Eastern Kaapvaal Craton,hibiting about 1000?Ma of crustal evolution from 3.66 to 2.67?Ga. The granitoid rocks predominantly consist of the tonalite–trondhjemite–granodiorite (TTG) association with true granites becoming abundant at about 3?Ga. Greenstones are represented by the well-preserved and well-studied 3.54–3.2?Ga B作者: Serenity 時(shí)間: 2025-3-27 19:00 作者: 反饋 時(shí)間: 2025-3-28 01:33
The Long Perspectives,f the sentimentalists which would later thrive on a misreading of his own work) he, like Shakespeare, knew that such a life in its purest form must be that of ‘unaccommodated man’, exposed to the alien and uncaring processes of the universe at large; no response to the landscape which failed to acknowledge the fact could be adequate.作者: 費(fèi)解 時(shí)間: 2025-3-28 05:48 作者: 謊言 時(shí)間: 2025-3-28 08:05 作者: 持久 時(shí)間: 2025-3-28 12:59
Dennis Ahrholdt,Goetz Greve,Gregor Hopfbook not only provides beginners with an introduction to machine learning for applied sciences, enabling them to address global competitiveness and work on real-time technical challenges, it is also a valuable resource for scholars with domain knowledge..978-981-13-9384-6978-981-13-9382-2Series ISSN 2662-3366 Series E-ISSN 2662-3374 作者: Palpitation 時(shí)間: 2025-3-28 16:52
that the four basic problems of comparison discussed here — conceptualisation, strategies, theories and methods — are interrelated, and are separated here only for analytic convenience, it is also clear that, logically, the activity of conceptualisation is, in important respects, prior to the activ作者: craving 時(shí)間: 2025-3-28 21:37
1865-0929 neuron and related models; text computing using neural techniques; time-series and related models; and unsupervised neural models..978-3-030-36807-4978-3-030-36808-1Series ISSN 1865-0929 Series E-ISSN 1865-0937 作者: 熒光 時(shí)間: 2025-3-29 02:44 作者: 范例 時(shí)間: 2025-3-29 04:14
Logistical and Operational Practice in the Regulated Bioanalysis Laboratory,d communications requires operational structures to evolve accordingly. These and other variables discussed in this chapter demonstrate the operational and logistical differences between different types of bioanalytical laboratories. Despite the structural differences, there are also some common log作者: 甜得發(fā)膩 時(shí)間: 2025-3-29 09:36
Jeffrey M. Brandsma,Douglas P. Hobson abwandlungsreichen Modulation der Laute kann dann eine ?Sprache” entstehen, wenn den einzelnen Laut- und Klanggebilden und ihren Gruppierungen eine besondere und feststehende Bedeutung beigemessen wird..
