صورة الغلاف المحلية
عرض عادي
Applied unsupervised learning with Python : discover hidden patterns and relationships in unstructured data with Python / Benjamin Johnston, Aaron Jones and Christopher Kruger
نوع المادة :
نصاللغة: الإنجليزية الناشر:Birmingham, UK : Packt Publishing, 2019وصف:vii, 455, [4] pages : illustrations ; 24 cmنوع المحتوى:- text
- unmediated
- volume
- 9781789958379
- 1789958377
- 9781789952292
- QA76.73.P98 J646 2019
المحتويات:
ملخص:Starting with the basics, Applied Unsupervised Learning with Python explains various techniques that you can apply to your data using the powerful Python libraries so that your unlabeled data reveals solutions to all your business questions.
1. Introduction to Clustering.-- 2. Hierarchical Clustering.-- 3. Neighborhood Approaches and DBSCAN.-- 4. Dimension Reduction and PCA .-- 5. Autoencoders.-- 6. t-Distributed Stochastic Neighbor Embedding (t-SNE).--7. Topic Modeling.-- 8. Market Basket Analysis.-- 9. Hotspot Analysis .--Appendix.
| نوع المادة | المكتبة الحالية | رقم الطلب | رقم النسخة | حالة | تاريخ الإستحقاق | الباركود | |
|---|---|---|---|---|---|---|---|
كتاب
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UAE Federation Library | مكتبة اتحاد الإمارات General Collection | المجموعات العامة | QA76.73.P98 J646 2019 (إستعراض الرف(يفتح أدناه)) | C.1 | Library Use Only | داخل المكتبة فقط | 30030000005964 | ||
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كتاب
|
UAE Federation Library | مكتبة اتحاد الإمارات General Collection | المجموعات العامة | QA76.73.P98 J646 2019 (إستعراض الرف(يفتح أدناه)) | C.2 | المتاح | 30030000005963 |
Browsing UAE Federation Library | مكتبة اتحاد الإمارات shelves, Shelving location: General Collection | المجموعات العامة إغلاق مستعرض الرف(يخفي مستعرض الرف)
| QA76.73.P98 H67 2019 Python for everyone / | QA76.73.P98 H67 2019 Python for everyone / | QA76.73.P98 J646 2019 Applied unsupervised learning with Python : discover hidden patterns and relationships in unstructured data with Python / | QA76.73.P98 J646 2019 Applied unsupervised learning with Python : discover hidden patterns and relationships in unstructured data with Python / | QA76.73.P98 K3784 2019 Mobile artificial intelligence projects : develop seven projects on your smartphone using artificial intelligence and deep learning techniques / | QA76.73.P98 K3784 2019 Mobile artificial intelligence projects : develop seven projects on your smartphone using artificial intelligence and deep learning techniques / | QA76.73.P98 K67 2018 Python graphics : a reference for creating 2D and 3D images / |
Includes bibliographical references
1. Introduction to Clustering.-- 2. Hierarchical Clustering.-- 3. Neighborhood Approaches and DBSCAN.-- 4. Dimension Reduction and PCA .-- 5. Autoencoders.-- 6. t-Distributed Stochastic Neighbor Embedding (t-SNE).--7. Topic Modeling.-- 8. Market Basket Analysis.-- 9. Hotspot Analysis .--Appendix.
Starting with the basics, Applied Unsupervised Learning with Python explains various techniques that you can apply to your data using the powerful Python libraries so that your unlabeled data reveals solutions to all your business questions.
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