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LinkedIn Learning - Data Science Foundations Fundamentals
magnet:?xt=urn:btih:aa26b4a778c2a05c199cc2f082afa5924755c63c&dn=LinkedIn Learning - Data Science Foundations Fundamentals
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文件列表详情
aa26b4a778c2a05c199cc2f082afa5924755c63c
infohash:
45
文件数量
703.09 MB
文件大小
2023-1-23 21:44
创建日期
2024-6-20 00:33
最后访问
相关分词
LinkedIn
Learning
-
Data
Science
Foundations
Fundamentals
[10] 9. Acting on Data Science/[1] Interpretability.mp4 9.3 MB
[10] 9. Acting on Data Science/[2] Actionable insights.mp4 8.24 MB
[11] Conclusion/[1] Next steps.mp4 9.54 MB
[1] Introduction/[1] The fundamentals of data science.mp4 11.81 MB
[2] 1. What Is Data Science/[1] Supply and demand for data science.mp4 8.28 MB
[2] 1. What Is Data Science/[2] The data science Venn diagram.mp4 8.64 MB
[2] 1. What Is Data Science/[3] The data science pathway.mp4 23.22 MB
[2] 1. What Is Data Science/[4] Roles and teams in data science.mp4 14.03 MB
[3] 2. The Place of Data Science in the Data Universe/[1] Artificial intelligence.mp4 29.55 MB
[3] 2. The Place of Data Science in the Data Universe/[2] Machine learning.mp4 29.96 MB
[3] 2. The Place of Data Science in the Data Universe/[3] Deep learning neural networks.mp4 30.53 MB
[3] 2. The Place of Data Science in the Data Universe/[4] Big data.mp4 14.91 MB
[3] 2. The Place of Data Science in the Data Universe/[5] Predictive analytics.mp4 12.04 MB
[3] 2. The Place of Data Science in the Data Universe/[6] Prescriptive analytics.mp4 13.98 MB
[3] 2. The Place of Data Science in the Data Universe/[7] Business intelligence.mp4 11.08 MB
[4] 3. Ethics and Agency/[1] Legal, ethical, and social issues of data science.mp4 12.59 MB
[4] 3. Ethics and Agency/[2] Agency of algorithms and decision-makers.mp4 12.62 MB
[5] 4. Sources of Data/[1] Data preparation.mp4 15 MB
[5] 4. Sources of Data/[2] In-house data.mp4 6.05 MB
[5] 4. Sources of Data/[3] Open data.mp4 20.52 MB
[5] 4. Sources of Data/[4] APIs.mp4 10.55 MB
[5] 4. Sources of Data/[5] Scraping data.mp4 29.71 MB
[5] 4. Sources of Data/[6] Creating data.mp4 14.73 MB
[5] 4. Sources of Data/[7] Passive collection of training data.mp4 13.21 MB
[5] 4. Sources of Data/[8] Self-generated data.mp4 13.97 MB
[6] 5. Sources of Rules/[1] The enumeration of explicit rules.mp4 12.66 MB
[6] 5. Sources of Rules/[2] The derivation of rules from data analysis.mp4 23.83 MB
[6] 5. Sources of Rules/[3] The generation of implicit rules.mp4 9.18 MB
[7] 6. Tools for Data Science/[1] Applications for data analysis.mp4 15.15 MB
[7] 6. Tools for Data Science/[2] Languages for data science.mp4 12.86 MB
[7] 6. Tools for Data Science/[3] Machine learning as a service.mp4 11.26 MB
[8] 7. Mathematics for Data Science/[1] Algebra.mp4 14.83 MB
[8] 7. Mathematics for Data Science/[2] Calculus.mp4 8.66 MB
[8] 7. Mathematics for Data Science/[3] Optimization and the combinatorial explosion.mp4 13.91 MB
[8] 7. Mathematics for Data Science/[4] Bayes' theorem.mp4 10.58 MB
[9] 8. Analyses for Data Science/[10] Aggregating models.mp4 15.04 MB
[9] 8. Analyses for Data Science/[1] Descriptive analyses.mp4 23.19 MB
[9] 8. Analyses for Data Science/[2] Predictive models.mp4 24.51 MB
[9] 8. Analyses for Data Science/[3] Trend analysis.mp4 19.19 MB
[9] 8. Analyses for Data Science/[4] Clustering.mp4 18.41 MB
[9] 8. Analyses for Data Science/[5] Classifying.mp4 13.01 MB
[9] 8. Analyses for Data Science/[6] Anomaly detection.mp4 18.19 MB
[9] 8. Analyses for Data Science/[7] Dimensionality reduction.mp4 19.46 MB
[9] 8. Analyses for Data Science/[8] Feature selection and creation.mp4 16.9 MB
[9] 8. Analyses for Data Science/[9] Validating models.mp4 18.2 MB
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