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~Get Your Files Here !/05 - 4. Dependency Management/02 - Specifying and installing dependencies.mp4 7.1 MB
~Get Your Files Here !/06 - 5. Running in Production/04 - Securing your code.mp4 5.8 MB
~Get Your Files Here !/04 - 3. Testing Your Code/04 - Test fixtures.mp4 5.5 MB
~Get Your Files Here !/02 - 1. Notebooks to Production/01 - Understanding production.mp4 5.4 MB
~Get Your Files Here !/04 - 3. Testing Your Code/01 - Why testing is important.mp4 5.0 MB
~Get Your Files Here !/02 - 1. Notebooks to Production/03 - Where notebooks come short.mp4 4.8 MB
~Get Your Files Here !/04 - 3. Testing Your Code/05 - Continuous integration.mp4 4.7 MB
~Get Your Files Here !/06 - 5. Running in Production/01 - Logging and metrics.mp4 4.5 MB
~Get Your Files Here !/05 - 4. Dependency Management/03 - Separating test dependencies.mp4 4.3 MB
~Get Your Files Here !/06 - 5. Running in Production/02 - Configuration.mp4 4.0 MB
~Get Your Files Here !/04 - 3. Testing Your Code/03 - Parametrized tests.mp4 3.9 MB
~Get Your Files Here !/03 - 2. Organizing Your Code/04 - Main.mp4 3.8 MB
~Get Your Files Here !/04 - 3. Testing Your Code/07 - Solution Test tags.mp4 3.7 MB
~Get Your Files Here !/02 - 1. Notebooks to Production/02 - Where notebooks excel.mp4 3.3 MB
~Get Your Files Here !/06 - 5. Running in Production/06 - Solution Make the monthly report production ready.mp4 3.1 MB
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- 【影视】 Data Science Made Easy Hands-On Analytics with No-Code Software Tool KNIME
- 收录时间:2025-04-02 文档个数:56 文档大小:1.5 GB 最近下载:2025-05-15 人气:761 磁力链接
Lesson 1 Data Science Overview/005. 1.4 AIML Evolution.mp4 102.2 MB
Lesson 3 ML Model Development with KNIME/002. 3.1 Data Ingestion and Preparation Part 1.mp4 98.0 MB
Lesson 1 Data Science Overview/003. 1.2 Data Science Process.mp4 95.3 MB
Lesson 2 Data Science Tools/003. 2.2 Introduction to KNIME AP.mp4 91.6 MB
Lesson 2 Data Science Tools/006. 2.5 KNIME Demo with Iris Dataset Part 2.mp4 88.5 MB
Lesson 4 Best Practices in Data Science and AIML/005. 4.4 Model Explainability (XAI).mp4 84.4 MB
Lesson 4 Best Practices in Data Science and AIML/002. 4.1 Data Balancing for Class Imbalance Problem.mp4 83.1 MB
Lesson 2 Data Science Tools/002. 2.1 Tool Landscape.mp4 79.7 MB
Lesson 5 Text Analytics/004. 5.3 TM Applications Sentiment Analysis.mp4 79.2 MB
Lesson 1 Data Science Overview/002. 1.1 Definition, Terminology, and a Simple Taxonomy.mp4 74.1 MB
Lesson 1 Data Science Overview/004. 1.3 Data Science Methods and Algorithms.mp4 72.2 MB
Lesson 4 Best Practices in Data Science and AIML/004. 4.3 Model Ensembles (with Bagging & Boosting).mp4 64.9 MB
Lesson 5 Text Analytics/003. 5.2 Text Mining Process.mp4 58.1 MB
Lesson 3 ML Model Development with KNIME/003. 3.2 Data Ingestion and Preparation Part 2.mp4 54.7 MB
Lesson 5 Text Analytics/005. 5.4 TM Applications Topic Modeling.mp4 52.0 MB
Lesson 4 Best Practices in Data Science and AIML/003. 4.2 Cross Validation for Bias-Variance Tradeoff.mp4 50.8 MB
Lesson 2 Data Science Tools/005. 2.4 KNIME Demo with Iris Dataset Part 1.mp4 43.0 MB
Lesson 3 ML Model Development with KNIME/004. 3.3 ML Model Building and Testing.mp4 42.4 MB
Lesson 5 Text Analytics/002. 5.1 Overview of Text Mining and Natural Language Processing (NLP).mp4 35.1 MB
Lesson 3 ML Model Development with KNIME/005. 3.4 Comparative Assessment.mp4 30.8 MB
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