[UdemyCourseDownloader] Machine Learning and AI Foundations Predictive Modeling Strategy at Scale

磁力链接/BT种子名称

[UdemyCourseDownloader] Machine Learning and AI Foundations Predictive Modeling Strategy at Scale

磁力链接/BT种子简介

种子哈希：fa243f5243c3c87ace6875365dd884a44d3f5d6c
文件大小：163.99M
已经下载：523次
下载速度：极快
收录时间：2023-12-24
最近下载：2024-11-20

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文件列表

  • 29 - What is model monitoring.mp4 11.7 MB
  • 26 - Batch vs. real-time scoring.mp4 10.0 MB
  • 30 - How often should you rebuild.mp4 9.4 MB
  • 10 - Assessing data.mp4 9.3 MB
  • 22 - Modeling with missing data.mp4 8.7 MB
  • 24 - Scoring a black box model.mp4 8.4 MB
  • 13 - Data and the data scientist.mp4 8.3 MB
  • 12 - Seasonality and time alignment.mp4 7.3 MB
  • 05 - The stages of predictive analytics data.mp4 6.9 MB
  • 09 - Who truly has big data.mp4 6.7 MB
  • 01 - Scaling machine learning initiatives.mp4 6.5 MB
  • 04 - The nine big data bottlenecks.mp4 6.1 MB
  • 23 - Scoring traditional ML models.mp4 5.1 MB
  • 27 - Data prep and scoring.mp4 5.0 MB
  • 17 - Understanding the modeling process.mp4 4.9 MB
  • 25 - Scoring an ensemble.mp4 4.7 MB
  • 16 - Feature engineering.mp4 4.4 MB
  • 21 - How to sample properly.mp4 4.4 MB
  • 28 - Combining batch and real-time scoring.mp4 4.0 MB
  • 07 - How much data do I need.mp4 3.9 MB
  • 03 - Data and supervised machine learning.mp4 3.9 MB
  • 20 - Slow algorithms More models.mp4 3.8 MB
  • 11 - Selecting Data that should be left out.mp4 3.7 MB
  • 02 - Defining terms.mp4 3.6 MB
  • 14 - Aggregate and restructure.mp4 3.6 MB
  • 08 - Balancing.mp4 3.4 MB
  • 15 - Dummy coding.mp4 3.2 MB
  • 19 - Slow algorithms More calculations.mp4 3.2 MB
  • 18 - Slow algorithms Brute force.mp4 3.0 MB
  • 06 - Why you might have too little data.mp4 2.9 MB
  • 31 - Next steps.mp4 1.8 MB
  • 26 - Batch vs. real-time scoring.en.srt 8.0 kB
  • 29 - What is model monitoring.en.srt 7.5 kB
  • 12 - Seasonality and time alignment.en.srt 7.2 kB
  • 30 - How often should you rebuild.en.srt 7.2 kB
  • 04 - The nine big data bottlenecks.en.srt 6.6 kB
  • 22 - Modeling with missing data.en.srt 6.1 kB
  • 09 - Who truly has big data.en.srt 6.1 kB
  • 10 - Assessing data.en.srt 6.1 kB
  • 27 - Data prep and scoring.en.srt 5.5 kB
  • 17 - Understanding the modeling process.en.srt 5.4 kB
  • 24 - Scoring a black box model.en.srt 5.2 kB
  • 05 - The stages of predictive analytics data.en.srt 5.2 kB
  • 23 - Scoring traditional ML models.en.srt 5.2 kB
  • 16 - Feature engineering.en.srt 5.1 kB
  • 13 - Data and the data scientist.en.srt 4.8 kB
  • 21 - How to sample properly.en.srt 4.4 kB
  • 20 - Slow algorithms More models.en.srt 4.1 kB
  • 07 - How much data do I need.en.srt 3.8 kB
  • 15 - Dummy coding.en.srt 3.8 kB
  • 03 - Data and supervised machine learning.en.srt 3.7 kB
  • 11 - Selecting Data that should be left out.en.srt 3.7 kB
  • 14 - Aggregate and restructure.en.srt 3.5 kB
  • 08 - Balancing.en.srt 3.4 kB
  • 18 - Slow algorithms Brute force.en.srt 3.2 kB
  • 02 - Defining terms.en.srt 3.2 kB
  • 25 - Scoring an ensemble.en.srt 3.2 kB
  • 28 - Combining batch and real-time scoring.en.srt 3.0 kB
  • 06 - Why you might have too little data.en.srt 3.0 kB
  • 01 - Scaling machine learning initiatives.en.srt 3.0 kB
  • 19 - Slow algorithms More calculations.en.srt 2.9 kB
  • 31 - Next steps.en.srt 1.6 kB
  • udemycoursedownloader.com.url 132 Bytes
  • Udemy Course downloader.txt 94 Bytes

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