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[FreeCourseLab.com] Udemy - Introduction to Machine Learning for Data Science

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种子名称: [FreeCourseLab.com] Udemy - Introduction to Machine Learning for Data Science
文件类型: 视频
文件数目: 61个文件
文件大小: 2.45 GB
收录时间: 2019-3-14 19:52
已经下载: 3
资源热度: 111
最近下载: 2024-10-3 20:11

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[FreeCourseLab.com] Udemy - Introduction to Machine Learning for Data Science.torrent
  • 1. Introduction/1. Course Promotion Video.mp431.88MB
  • 1. Introduction/2. A special message for hard of hearing and ESL students.mp418.05MB
  • 1. Introduction/3. Thank you for investing in this Course!.mp414.74MB
  • 1. Introduction/4. Course Overview.mp436.81MB
  • 1. Introduction/5. Secret sauce inside! How to get the most out of this course..mp424.33MB
  • 10. Section 4 - Bonus course - Machine Learning in Python and Jupyter for Beginners/1. Foundations of Machine Learning and Data Science - Definitions and concepts..mp494.45MB
  • 10. Section 4 - Bonus course - Machine Learning in Python and Jupyter for Beginners/2. Foundations of Machine Learning and Data Science - Machine Learning Workflow.mp475.6MB
  • 10. Section 4 - Bonus course - Machine Learning in Python and Jupyter for Beginners/3. Foundations of Machine Learning and Data Science - Algorithms, concepts and more.mp4121.31MB
  • 11. Section 5 -Bonus course - Machine Learning in Python and Jupyter for Beginners/1. Introducing the essential modules for Machine Learning, and NumPy Basics.mp494.93MB
  • 11. Section 5 -Bonus course - Machine Learning in Python and Jupyter for Beginners/2. Pandas and Matplotlib.mp498.99MB
  • 11. Section 5 -Bonus course - Machine Learning in Python and Jupyter for Beginners/3. Analysis using Pandas, plotting in Matplotlib, intro to SciPy and Scikit-learn.mp483.74MB
  • 12. Section 6 - Bonus course - Machine Learning in Python and Jupyter for Beginners/1. A Titanic Example - Getting our start..mp488.82MB
  • 12. Section 6 - Bonus course - Machine Learning in Python and Jupyter for Beginners/2. A Titanic Example - Understanding the data set..mp473.44MB
  • 12. Section 6 - Bonus course - Machine Learning in Python and Jupyter for Beginners/3. A Titanic Example - Understanding the data set in regards to survival.mp454.74MB
  • 12. Section 6 - Bonus course - Machine Learning in Python and Jupyter for Beginners/4. A Titanic Example - Preparing the right data and applying a basic algorithm.mp4114.56MB
  • 12. Section 6 - Bonus course - Machine Learning in Python and Jupyter for Beginners/5. A Titanic Example - Applying regression algorithms..mp450.24MB
  • 12. Section 6 - Bonus course - Machine Learning in Python and Jupyter for Beginners/6. A Titanic Example - Applying Decision Trees (example of overfit and underfit).mp456.13MB
  • 13. Section 7 -Bonus course - Machine Learning in Python and Jupyter for Beginners/1. Conclusions - for our Titanic Example, important concepts and where to go next!.mp4101.36MB
  • 14. Retired Lectures/1. #4 - Secret sauce inside! How to get the most out of this course.mp430.83MB
  • 14. Retired Lectures/2. Computer Science - Definition Revisited & The Greatest lie ever SOLD.....mp432.3MB
  • 2. Core Concepts/1. Core Concepts Overview.mp430.16MB
  • 2. Core Concepts/10. What is Machine Learning - Part 1 - The ideas.mp438.38MB
  • 2. Core Concepts/11. What is Machine Learning - Part 2 - An Example.mp424.29MB
  • 2. Core Concepts/12. What is data science.mp418.48MB
  • 2. Core Concepts/13. Recap & How do these relate to each other.mp410.88MB
  • 2. Core Concepts/2. Computer Science - the `Train Wreck' Definition.mp43.55MB
  • 2. Core Concepts/3. What's Data I can see data everywhere!.mp422.75MB
  • 2. Core Concepts/4. Structured vs Unstructured Data.mp49.11MB
  • 2. Core Concepts/6. Computer Science - Definition Revisited & The Greatest lie ever SOLD.....mp432.51MB
  • 2. Core Concepts/7. What's big data.mp424.17MB
  • 2. Core Concepts/9. What is Artificial Intelligence (AI).mp443.21MB
  • 3. Impacts, Importance and examples/1. Impacts, Importance and examples - Overview.mp412.88MB
  • 3. Impacts, Importance and examples/2. Why is this important now.mp425.87MB
  • 3. Impacts, Importance and examples/3. Computers exploding! - The explosive growth of computer power explained..mp472.52MB
  • 3. Impacts, Importance and examples/4. What problems does Machine Learning Solve.mp417.1MB
  • 3. Impacts, Importance and examples/5. Where it's transforming our lives.mp433.12MB
  • 4. The Machine Learning Process/1. The Machine Learning Process - Overview.mp420.01MB
  • 4. The Machine Learning Process/2. 5 Step Machine Learning Process Overview.mp46.24MB
  • 4. The Machine Learning Process/3. 1 - Asking the right question.mp48.12MB
  • 4. The Machine Learning Process/4. 2 - Identifying, obtaining, and preparing the right data.mp432.14MB
  • 4. The Machine Learning Process/5. 3 - Identifying and applying a ML Algorithm.mp431.6MB
  • 4. The Machine Learning Process/6. 4 - Evaluating the performance of the model and adjusting.mp411.39MB
  • 4. The Machine Learning Process/7. 5 - Using and presenting the model.mp45.3MB
  • 5. How to apply Machine Learning for Data Science/1. How to apply Machine Learning for Data Science - Overview.mp45.5MB
  • 5. How to apply Machine Learning for Data Science/2. Where to begin your journey.mp43.43MB
  • 5. How to apply Machine Learning for Data Science/3. Common platforms and tools for Data Science.mp46.31MB
  • 5. How to apply Machine Learning for Data Science/4. Data Science using - R.mp45.49MB
  • 5. How to apply Machine Learning for Data Science/5. Data Science using - Python.mp47.33MB
  • 5. How to apply Machine Learning for Data Science/6. Data Science using SQL.mp45.63MB
  • 5. How to apply Machine Learning for Data Science/7. Data Science using Excel.mp45.03MB
  • 5. How to apply Machine Learning for Data Science/8. Data Science using RapidMiner.mp43.31MB
  • 5. How to apply Machine Learning for Data Science/9. Cautionary Tales.mp44.61MB
  • 6. Conclusion/1. All done! What's next.mp46.22MB
  • 7. Section 1 -Bonus course - Machine Learning in Python and Jupyter for Beginners/1. Introduction and Anaconda Installation.mp477.79MB
  • 7. Section 1 -Bonus course - Machine Learning in Python and Jupyter for Beginners/2. What will we cover!.mp496.28MB
  • 7. Section 1 -Bonus course - Machine Learning in Python and Jupyter for Beginners/3. Introduction and Setup.mp4119.75MB
  • 8. Section 2 -Bonus course - Machine Learning in Python and Jupyter for Beginners/1. Crash course in Python - Beginning concepts.mp461.63MB
  • 8. Section 2 -Bonus course - Machine Learning in Python and Jupyter for Beginners/2. Crash course in Python - Strings, Slices and Lists!.mp467.44MB
  • 8. Section 2 -Bonus course - Machine Learning in Python and Jupyter for Beginners/3. Crash course in Python - Expressions, Operators, Conditions and Loops.mp452.14MB
  • 8. Section 2 -Bonus course - Machine Learning in Python and Jupyter for Beginners/4. Crash course in Python - Functions, Scope, Dictionaries and more!.mp457.04MB
  • 9. Section 3 - Bonus course - Machine Learning in Python and Jupyter for Beginners/1. Hands on Running Python.mp495.34MB