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LinkedIn Learning - Data Science Foundations Fundamentals [CoursesGhar]
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2023-10-29 01:10
2024-11-22 16:40
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703.09 MB
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磁力链接
magnet:?xt=urn:btih:2107b82bb0f0855115dbbd21bfb63c04aef88099
迅雷链接
thunder://QUFtYWduZXQ6P3h0PXVybjpidGloOjIxMDdiODJiYjBmMDg1NTExNWRiYmQyMWJmYjYzYzA0YWVmODgwOTlaWg==
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LinkedIn
Learning
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Data
Science
Foundations
Fundamentals
CoursesGhar
文件列表
[10] 9. Acting on Data Science/[1] Interpretability.mp4
9.3MB
[10] 9. Acting on Data Science/[2] Actionable insights.mp4
8.24MB
[11] Conclusion/[1] Next steps.mp4
9.54MB
[1] Introduction/[1] The fundamentals of data science.mp4
11.81MB
[2] 1. What Is Data Science/[1] Supply and demand for data science.mp4
8.28MB
[2] 1. What Is Data Science/[2] The data science Venn diagram.mp4
8.64MB
[2] 1. What Is Data Science/[3] The data science pathway.mp4
23.22MB
[2] 1. What Is Data Science/[4] Roles and teams in data science.mp4
14.03MB
[3] 2. The Place of Data Science in the Data Universe/[1] Artificial intelligence.mp4
29.55MB
[3] 2. The Place of Data Science in the Data Universe/[2] Machine learning.mp4
29.96MB
[3] 2. The Place of Data Science in the Data Universe/[3] Deep learning neural networks.mp4
30.53MB
[3] 2. The Place of Data Science in the Data Universe/[4] Big data.mp4
14.91MB
[3] 2. The Place of Data Science in the Data Universe/[5] Predictive analytics.mp4
12.04MB
[3] 2. The Place of Data Science in the Data Universe/[6] Prescriptive analytics.mp4
13.98MB
[3] 2. The Place of Data Science in the Data Universe/[7] Business intelligence.mp4
11.08MB
[4] 3. Ethics and Agency/[1] Legal, ethical, and social issues of data science.mp4
12.59MB
[4] 3. Ethics and Agency/[2] Agency of algorithms and decision-makers.mp4
12.62MB
[5] 4. Sources of Data/[1] Data preparation.mp4
15MB
[5] 4. Sources of Data/[2] In-house data.mp4
6.05MB
[5] 4. Sources of Data/[3] Open data.mp4
20.52MB
[5] 4. Sources of Data/[4] APIs.mp4
10.55MB
[5] 4. Sources of Data/[5] Scraping data.mp4
29.71MB
[5] 4. Sources of Data/[6] Creating data.mp4
14.73MB
[5] 4. Sources of Data/[7] Passive collection of training data.mp4
13.21MB
[5] 4. Sources of Data/[8] Self-generated data.mp4
13.97MB
[6] 5. Sources of Rules/[1] The enumeration of explicit rules.mp4
12.66MB
[6] 5. Sources of Rules/[2] The derivation of rules from data analysis.mp4
23.83MB
[6] 5. Sources of Rules/[3] The generation of implicit rules.mp4
9.18MB
[7] 6. Tools for Data Science/[1] Applications for data analysis.mp4
15.15MB
[7] 6. Tools for Data Science/[2] Languages for data science.mp4
12.86MB
[7] 6. Tools for Data Science/[3] Machine learning as a service.mp4
11.26MB
[8] 7. Mathematics for Data Science/[1] Algebra.mp4
14.83MB
[8] 7. Mathematics for Data Science/[2] Calculus.mp4
8.66MB
[8] 7. Mathematics for Data Science/[3] Optimization and the combinatorial explosion.mp4
13.91MB
[8] 7. Mathematics for Data Science/[4] Bayes' theorem.mp4
10.58MB
[9] 8. Analyses for Data Science/[10] Aggregating models.mp4
15.04MB
[9] 8. Analyses for Data Science/[1] Descriptive analyses.mp4
23.19MB
[9] 8. Analyses for Data Science/[2] Predictive models.mp4
24.51MB
[9] 8. Analyses for Data Science/[3] Trend analysis.mp4
19.19MB
[9] 8. Analyses for Data Science/[4] Clustering.mp4
18.41MB
[9] 8. Analyses for Data Science/[5] Classifying.mp4
13.01MB
[9] 8. Analyses for Data Science/[6] Anomaly detection.mp4
18.19MB
[9] 8. Analyses for Data Science/[7] Dimensionality reduction.mp4
19.46MB
[9] 8. Analyses for Data Science/[8] Feature selection and creation.mp4
16.9MB
[9] 8. Analyses for Data Science/[9] Validating models.mp4
18.2MB
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