LinkedIn Learning - Data Science Foundations Fundamentals [CoursesGhar]

磁力链接/BT种子名称

LinkedIn Learning - Data Science Foundations Fundamentals [CoursesGhar]

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种子哈希：2107b82bb0f0855115dbbd21bfb63c04aef88099
文件大小：703.48M
已经下载：992次
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收录时间：2022-02-06
最近下载：2025-09-18

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文件列表

  • [3] 2. The Place of Data Science in the Data Universe/[3] Deep learning neural networks.mp4 32.0 MB
  • [3] 2. The Place of Data Science in the Data Universe/[2] Machine learning.mp4 31.4 MB
  • [5] 4. Sources of Data/[5] Scraping data.mp4 31.2 MB
  • [3] 2. The Place of Data Science in the Data Universe/[1] Artificial intelligence.mp4 31.0 MB
  • [9] 8. Analyses for Data Science/[2] Predictive models.mp4 25.7 MB
  • [6] 5. Sources of Rules/[2] The derivation of rules from data analysis.mp4 25.0 MB
  • [2] 1. What Is Data Science/[3] The data science pathway.mp4 24.4 MB
  • [9] 8. Analyses for Data Science/[1] Descriptive analyses.mp4 24.3 MB
  • [5] 4. Sources of Data/[3] Open data.mp4 21.5 MB
  • [9] 8. Analyses for Data Science/[7] Dimensionality reduction.mp4 20.4 MB
  • [9] 8. Analyses for Data Science/[3] Trend analysis.mp4 20.1 MB
  • [9] 8. Analyses for Data Science/[4] Clustering.mp4 19.3 MB
  • [9] 8. Analyses for Data Science/[9] Validating models.mp4 19.1 MB
  • [9] 8. Analyses for Data Science/[6] Anomaly detection.mp4 19.1 MB
  • [9] 8. Analyses for Data Science/[8] Feature selection and creation.mp4 17.7 MB
  • [7] 6. Tools for Data Science/[1] Applications for data analysis.mp4 15.9 MB
  • [9] 8. Analyses for Data Science/[10] Aggregating models.mp4 15.8 MB
  • [5] 4. Sources of Data/[1] Data preparation.mp4 15.7 MB
  • [3] 2. The Place of Data Science in the Data Universe/[4] Big data.mp4 15.6 MB
  • [8] 7. Mathematics for Data Science/[1] Algebra.mp4 15.6 MB
  • [5] 4. Sources of Data/[6] Creating data.mp4 15.4 MB
  • [2] 1. What Is Data Science/[4] Roles and teams in data science.mp4 14.7 MB
  • [3] 2. The Place of Data Science in the Data Universe/[6] Prescriptive analytics.mp4 14.7 MB
  • [5] 4. Sources of Data/[8] Self-generated data.mp4 14.6 MB
  • [8] 7. Mathematics for Data Science/[3] Optimization and the combinatorial explosion.mp4 14.6 MB
  • [5] 4. Sources of Data/[7] Passive collection of training data.mp4 13.9 MB
  • [9] 8. Analyses for Data Science/[5] Classifying.mp4 13.6 MB
  • [7] 6. Tools for Data Science/[2] Languages for data science.mp4 13.5 MB
  • [6] 5. Sources of Rules/[1] The enumeration of explicit rules.mp4 13.3 MB
  • [4] 3. Ethics and Agency/[2] Agency of algorithms and decision-makers.mp4 13.2 MB
  • [4] 3. Ethics and Agency/[1] Legal, ethical, and social issues of data science.mp4 13.2 MB
  • [3] 2. The Place of Data Science in the Data Universe/[5] Predictive analytics.mp4 12.6 MB
  • [1] Introduction/[1] The fundamentals of data science.mp4 12.4 MB
  • [7] 6. Tools for Data Science/[3] Machine learning as a service.mp4 11.8 MB
  • [3] 2. The Place of Data Science in the Data Universe/[7] Business intelligence.mp4 11.6 MB
  • [8] 7. Mathematics for Data Science/[4] Bayes' theorem.mp4 11.1 MB
  • [5] 4. Sources of Data/[4] APIs.mp4 11.1 MB
  • [11] Conclusion/[1] Next steps.mp4 10.0 MB
  • [10] 9. Acting on Data Science/[1] Interpretability.mp4 9.8 MB
  • [6] 5. Sources of Rules/[3] The generation of implicit rules.mp4 9.6 MB
  • [8] 7. Mathematics for Data Science/[2] Calculus.mp4 9.1 MB
  • [2] 1. What Is Data Science/[2] The data science Venn diagram.mp4 9.1 MB
  • [2] 1. What Is Data Science/[1] Supply and demand for data science.mp4 8.7 MB
  • [10] 9. Acting on Data Science/[2] Actionable insights.mp4 8.6 MB
  • [5] 4. Sources of Data/[2] In-house data.mp4 6.3 MB
  • [3] 2. The Place of Data Science in the Data Universe/[1] Artificial intelligence.srt 14.6 kB
  • [9] 8. Analyses for Data Science/[2] Predictive models.srt 14.1 kB
  • [3] 2. The Place of Data Science in the Data Universe/[2] Machine learning.srt 14.1 kB
  • [3] 2. The Place of Data Science in the Data Universe/[6] Prescriptive analytics.srt 14.0 kB
  • [8] 7. Mathematics for Data Science/[1] Algebra.srt 13.6 kB
  • [9] 8. Analyses for Data Science/[1] Descriptive analyses.srt 12.7 kB
  • [3] 2. The Place of Data Science in the Data Universe/[3] Deep learning neural networks.srt 12.6 kB
  • [9] 8. Analyses for Data Science/[3] Trend analysis.srt 11.9 kB
  • [8] 7. Mathematics for Data Science/[3] Optimization and the combinatorial explosion.srt 11.9 kB
  • [9] 8. Analyses for Data Science/[8] Feature selection and creation.srt 11.2 kB
  • [9] 8. Analyses for Data Science/[4] Clustering.srt 10.7 kB
  • [5] 4. Sources of Data/[6] Creating data.srt 10.6 kB
  • [9] 8. Analyses for Data Science/[5] Classifying.srt 10.6 kB
  • [9] 8. Analyses for Data Science/[7] Dimensionality reduction.srt 10.0 kB
  • [2] 1. What Is Data Science/[3] The data science pathway.srt 10.0 kB
  • [3] 2. The Place of Data Science in the Data Universe/[4] Big data.srt 9.8 kB
  • [5] 4. Sources of Data/[1] Data preparation.srt 9.7 kB
  • [9] 8. Analyses for Data Science/[6] Anomaly detection.srt 9.6 kB
  • [4] 3. Ethics and Agency/[2] Agency of algorithms and decision-makers.srt 9.3 kB
  • [5] 4. Sources of Data/[3] Open data.srt 9.0 kB
  • [5] 4. Sources of Data/[5] Scraping data.srt 8.7 kB
  • [3] 2. The Place of Data Science in the Data Universe/[5] Predictive analytics.srt 8.7 kB
  • [9] 8. Analyses for Data Science/[9] Validating models.srt 8.5 kB
  • [2] 1. What Is Data Science/[4] Roles and teams in data science.srt 8.3 kB
  • [7] 6. Tools for Data Science/[1] Applications for data analysis.srt 8.1 kB
  • [2] 1. What Is Data Science/[2] The data science Venn diagram.srt 8.1 kB
  • [8] 7. Mathematics for Data Science/[2] Calculus.srt 8.0 kB
  • [8] 7. Mathematics for Data Science/[4] Bayes' theorem.srt 8.0 kB
  • [4] 3. Ethics and Agency/[1] Legal, ethical, and social issues of data science.srt 8.0 kB
  • [6] 5. Sources of Rules/[2] The derivation of rules from data analysis.srt 7.8 kB
  • [6] 5. Sources of Rules/[1] The enumeration of explicit rules.srt 7.2 kB
  • [3] 2. The Place of Data Science in the Data Universe/[7] Business intelligence.srt 7.1 kB
  • [5] 4. Sources of Data/[7] Passive collection of training data.srt 7.1 kB
  • [9] 8. Analyses for Data Science/[10] Aggregating models.srt 7.0 kB
  • [2] 1. What Is Data Science/[1] Supply and demand for data science.srt 7.0 kB
  • [7] 6. Tools for Data Science/[2] Languages for data science.srt 6.7 kB
  • [6] 5. Sources of Rules/[3] The generation of implicit rules.srt 6.3 kB
  • [5] 4. Sources of Data/[8] Self-generated data.srt 5.9 kB
  • [10] 9. Acting on Data Science/[1] Interpretability.srt 5.9 kB
  • [7] 6. Tools for Data Science/[3] Machine learning as a service.srt 5.8 kB
  • [11] Conclusion/[1] Next steps.srt 5.0 kB
  • [10] 9. Acting on Data Science/[2] Actionable insights.srt 5.0 kB
  • [5] 4. Sources of Data/[4] APIs.srt 4.8 kB
  • [5] 4. Sources of Data/[2] In-house data.srt 3.8 kB
  • [1] Introduction/[1] The fundamentals of data science.srt 2.5 kB
  • !! Info !!.txt 1.1 kB
  • [TGx]Downloaded from torrentgalaxy.to .txt 564 Bytes
  • !! Join Us On Telgram !!.txt 287 Bytes
  • !!! Please Support !!! [CoursesGhar.Com].txt 197 Bytes
  • telegram @coursesghar.url 138 Bytes
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