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

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

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种子哈希：81b528ea70ec88bc19d7a4cdbbdbd807aa8f16e1
文件大小： 2.45G
已经下载：997次
下载速度：极快
收录时间：2021-04-29
最近下载：2024-12-19

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文件列表

  • 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.mp4 127.2 MB
  • 7. Section 1 -Bonus course - Machine Learning in Python and Jupyter for Beginners/3. Introduction and Setup.mp4 125.6 MB
  • 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.mp4 120.1 MB
  • 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!.mp4 106.3 MB
  • 11. Section 5 -Bonus course - Machine Learning in Python and Jupyter for Beginners/2. Pandas and Matplotlib.mp4 103.8 MB
  • 7. Section 1 -Bonus course - Machine Learning in Python and Jupyter for Beginners/2. What will we cover!.mp4 101.0 MB
  • 9. Section 3 - Bonus course - Machine Learning in Python and Jupyter for Beginners/1. Hands on Running Python.mp4 100.0 MB
  • 11. Section 5 -Bonus course - Machine Learning in Python and Jupyter for Beginners/1. Introducing the essential modules for Machine Learning, and NumPy Basics.mp4 99.5 MB
  • 10. Section 4 - Bonus course - Machine Learning in Python and Jupyter for Beginners/1. Foundations of Machine Learning and Data Science - Definitions and concepts..mp4 99.0 MB
  • 12. Section 6 - Bonus course - Machine Learning in Python and Jupyter for Beginners/1. A Titanic Example - Getting our start..mp4 93.1 MB
  • 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.mp4 87.8 MB
  • 7. Section 1 -Bonus course - Machine Learning in Python and Jupyter for Beginners/1. Introduction and Anaconda Installation.mp4 81.6 MB
  • 10. Section 4 - Bonus course - Machine Learning in Python and Jupyter for Beginners/2. Foundations of Machine Learning and Data Science - Machine Learning Workflow.mp4 79.3 MB
  • 12. Section 6 - Bonus course - Machine Learning in Python and Jupyter for Beginners/2. A Titanic Example - Understanding the data set..mp4 77.0 MB
  • 3. Impacts, Importance and examples/3. Computers exploding! - The explosive growth of computer power explained..mp4 76.0 MB
  • 8. Section 2 -Bonus course - Machine Learning in Python and Jupyter for Beginners/2. Crash course in Python - Strings, Slices and Lists!.mp4 70.7 MB
  • 8. Section 2 -Bonus course - Machine Learning in Python and Jupyter for Beginners/1. Crash course in Python - Beginning concepts.mp4 64.6 MB
  • 8. Section 2 -Bonus course - Machine Learning in Python and Jupyter for Beginners/4. Crash course in Python - Functions, Scope, Dictionaries and more!.mp4 59.8 MB
  • 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).mp4 58.9 MB
  • 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.mp4 57.4 MB
  • 8. Section 2 -Bonus course - Machine Learning in Python and Jupyter for Beginners/3. Crash course in Python - Expressions, Operators, Conditions and Loops.mp4 54.7 MB
  • 12. Section 6 - Bonus course - Machine Learning in Python and Jupyter for Beginners/5. A Titanic Example - Applying regression algorithms..mp4 52.7 MB
  • 2. Core Concepts/9. What is Artificial Intelligence (AI).mp4 45.3 MB
  • 2. Core Concepts/10. What is Machine Learning - Part 1 - The ideas.mp4 40.2 MB
  • 1. Introduction/4. Course Overview.mp4 38.6 MB
  • 3. Impacts, Importance and examples/5. Where it's transforming our lives.mp4 34.7 MB
  • 2. Core Concepts/6. Computer Science - Definition Revisited & The Greatest lie ever SOLD.....mp4 34.1 MB
  • 14. Retired Lectures/2. Computer Science - Definition Revisited & The Greatest lie ever SOLD.....mp4 33.9 MB
  • 4. The Machine Learning Process/4. 2 - Identifying, obtaining, and preparing the right data.mp4 33.7 MB
  • 1. Introduction/1. Course Promotion Video.mp4 33.4 MB
  • 4. The Machine Learning Process/5. 3 - Identifying and applying a ML Algorithm.mp4 33.1 MB
  • 14. Retired Lectures/1. #4 - Secret sauce inside! How to get the most out of this course.mp4 32.3 MB
  • 2. Core Concepts/1. Core Concepts Overview.mp4 31.6 MB
  • 3. Impacts, Importance and examples/2. Why is this important now.mp4 27.1 MB
  • 1. Introduction/5. Secret sauce inside! How to get the most out of this course..mp4 25.5 MB
  • 2. Core Concepts/11. What is Machine Learning - Part 2 - An Example.mp4 25.5 MB
  • 2. Core Concepts/7. What's big data.mp4 25.3 MB
  • 2. Core Concepts/3. What's Data I can see data everywhere!.mp4 23.9 MB
  • 4. The Machine Learning Process/1. The Machine Learning Process - Overview.mp4 21.0 MB
  • 2. Core Concepts/12. What is data science.mp4 19.4 MB
  • 1. Introduction/2. A special message for hard of hearing and ESL students.mp4 18.9 MB
  • 3. Impacts, Importance and examples/4. What problems does Machine Learning Solve.mp4 17.9 MB
  • 1. Introduction/3. Thank you for investing in this Course!.mp4 15.5 MB
  • 3. Impacts, Importance and examples/1. Impacts, Importance and examples - Overview.mp4 13.5 MB
  • 4. The Machine Learning Process/6. 4 - Evaluating the performance of the model and adjusting.mp4 11.9 MB
  • 2. Core Concepts/13. Recap & How do these relate to each other.mp4 11.4 MB
  • 2. Core Concepts/4. Structured vs Unstructured Data.mp4 9.6 MB
  • 4. The Machine Learning Process/3. 1 - Asking the right question.mp4 8.5 MB
  • 5. How to apply Machine Learning for Data Science/5. Data Science using - Python.mp4 7.7 MB
  • 5. How to apply Machine Learning for Data Science/3. Common platforms and tools for Data Science.mp4 6.6 MB
  • 4. The Machine Learning Process/2. 5 Step Machine Learning Process Overview.mp4 6.5 MB
  • 6. Conclusion/1. All done! What's next.mp4 6.5 MB
  • 5. How to apply Machine Learning for Data Science/6. Data Science using SQL.mp4 5.9 MB
  • 5. How to apply Machine Learning for Data Science/1. How to apply Machine Learning for Data Science - Overview.mp4 5.8 MB
  • 5. How to apply Machine Learning for Data Science/4. Data Science using - R.mp4 5.8 MB
  • 4. The Machine Learning Process/7. 5 - Using and presenting the model.mp4 5.6 MB
  • 5. How to apply Machine Learning for Data Science/7. Data Science using Excel.mp4 5.3 MB
  • 5. How to apply Machine Learning for Data Science/9. Cautionary Tales.mp4 4.8 MB
  • 2. Core Concepts/2. Computer Science - the `Train Wreck' Definition.mp4 3.7 MB
  • 5. How to apply Machine Learning for Data Science/2. Where to begin your journey.mp4 3.6 MB
  • 5. How to apply Machine Learning for Data Science/8. Data Science using RapidMiner.mp4 3.5 MB
  • 15. Bonus Content/1.1 The startling breakthrough in Machine Learning from 2016.pdf.pdf.pdf 457.3 kB
  • 2. Core Concepts/13.1 byds-diagram.pdf.pdf 277.6 kB
  • 1. Introduction/4.1 Course Syllabus.pdf.pdf 270.9 kB
  • 8. Section 2 -Bonus course - Machine Learning in Python and Jupyter for Beginners/1.1 python_3.x_cheat_sheet.pdf.pdf 87.0 kB
  • 12. Section 6 - Bonus course - Machine Learning in Python and Jupyter for Beginners/6.2 tree-overfit.pdf.pdf 55.2 kB
  • 12. Section 6 - Bonus course - Machine Learning in Python and Jupyter for Beginners/6.1 tree-pruned.pdf.pdf 27.0 kB
  • 2. Core Concepts/9. What is Artificial Intelligence (AI).vtt 19.6 kB
  • 4. The Machine Learning Process/5. 3 - Identifying and applying a ML Algorithm.vtt 18.6 kB
  • 2. Core Concepts/10. What is Machine Learning - Part 1 - The ideas.vtt 18.4 kB
  • 4. The Machine Learning Process/4. 2 - Identifying, obtaining, and preparing the right data.vtt 18.2 kB
  • 3. Impacts, Importance and examples/3. Computers exploding! - The explosive growth of computer power explained..vtt 17.7 kB
  • 3. Impacts, Importance and examples/5. Where it's transforming our lives.vtt 15.3 kB
  • 2. Core Concepts/6. Computer Science - Definition Revisited & The Greatest lie ever SOLD.....vtt 14.9 kB
  • 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.vtt 13.0 kB
  • 12. Section 6 - Bonus course - Machine Learning in Python and Jupyter for Beginners/2. A Titanic Example - Understanding the data set..vtt 12.2 kB
  • 9. Section 3 - Bonus course - Machine Learning in Python and Jupyter for Beginners/1. Hands on Running Python.vtt 12.0 kB
  • 11. Section 5 -Bonus course - Machine Learning in Python and Jupyter for Beginners/2. Pandas and Matplotlib.vtt 11.5 kB
  • 14. Retired Lectures/2. Computer Science - Definition Revisited & The Greatest lie ever SOLD.....vtt 11.1 kB
  • 3. Impacts, Importance and examples/2. Why is this important now.vtt 11.1 kB
  • 12. Section 6 - Bonus course - Machine Learning in Python and Jupyter for Beginners/1. A Titanic Example - Getting our start..vtt 11.0 kB
  • 2. Core Concepts/11. What is Machine Learning - Part 2 - An Example.vtt 10.7 kB
  • 7. Section 1 -Bonus course - Machine Learning in Python and Jupyter for Beginners/3. Introduction and Setup.vtt 10.0 kB
  • 2. Core Concepts/7. What's big data.vtt 10.0 kB
  • 2. Core Concepts/3. What's Data I can see data everywhere!.vtt 9.0 kB
  • 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.vtt 8.8 kB
  • 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.vtt 8.7 kB
  • 8. Section 2 -Bonus course - Machine Learning in Python and Jupyter for Beginners/2. Crash course in Python - Strings, Slices and Lists!.vtt 8.6 kB
  • 11. Section 5 -Bonus course - Machine Learning in Python and Jupyter for Beginners/1. Introducing the essential modules for Machine Learning, and NumPy Basics.vtt 8.5 kB
  • 7. Section 1 -Bonus course - Machine Learning in Python and Jupyter for Beginners/2. What will we cover!.vtt 8.2 kB
  • 2. Core Concepts/12. What is data science.vtt 8.2 kB
  • 15. Bonus Content/1. Bonus Article - The startling breakthrough in Machine Learning from 2016..html 8.0 kB
  • 3. Impacts, Importance and examples/4. What problems does Machine Learning Solve.vtt 7.7 kB
  • 8. Section 2 -Bonus course - Machine Learning in Python and Jupyter for Beginners/1. Crash course in Python - Beginning concepts.vtt 7.5 kB
  • 1. Introduction/5. Secret sauce inside! How to get the most out of this course..vtt 7.2 kB
  • 4. The Machine Learning Process/6. 4 - Evaluating the performance of the model and adjusting.vtt 7.2 kB
  • 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!.vtt 7.1 kB
  • 8. Section 2 -Bonus course - Machine Learning in Python and Jupyter for Beginners/3. Crash course in Python - Expressions, Operators, Conditions and Loops.vtt 6.9 kB
  • 10. Section 4 - Bonus course - Machine Learning in Python and Jupyter for Beginners/1. Foundations of Machine Learning and Data Science - Definitions and concepts..vtt 6.8 kB
  • 8. Section 2 -Bonus course - Machine Learning in Python and Jupyter for Beginners/4. Crash course in Python - Functions, Scope, Dictionaries and more!.vtt 6.7 kB
  • 14. Retired Lectures/1. #4 - Secret sauce inside! How to get the most out of this course.vtt 6.6 kB
  • 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.vtt 6.6 kB
  • 10. Section 4 - Bonus course - Machine Learning in Python and Jupyter for Beginners/2. Foundations of Machine Learning and Data Science - Machine Learning Workflow.vtt 6.5 kB
  • 12. Section 6 - Bonus course - Machine Learning in Python and Jupyter for Beginners/5. A Titanic Example - Applying regression algorithms..vtt 6.4 kB
  • 7. Section 1 -Bonus course - Machine Learning in Python and Jupyter for Beginners/1. Introduction and Anaconda Installation.vtt 6.0 kB
  • 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).vtt 5.9 kB
  • 1. Introduction/4. Course Overview.vtt 5.6 kB
  • 2. Core Concepts/13. Recap & How do these relate to each other.vtt 5.4 kB
  • 4. The Machine Learning Process/3. 1 - Asking the right question.vtt 4.7 kB
  • 5. How to apply Machine Learning for Data Science/5. Data Science using - Python.vtt 3.8 kB
  • 1. Introduction/1. Course Promotion Video.vtt 3.7 kB
  • 2. Core Concepts/4. Structured vs Unstructured Data.vtt 3.7 kB
  • 5. How to apply Machine Learning for Data Science/4. Data Science using - R.vtt 3.4 kB
  • 4. The Machine Learning Process/7. 5 - Using and presenting the model.vtt 3.3 kB
  • 5. How to apply Machine Learning for Data Science/3. Common platforms and tools for Data Science.vtt 3.2 kB
  • 5. How to apply Machine Learning for Data Science/7. Data Science using Excel.vtt 3.0 kB
  • 5. How to apply Machine Learning for Data Science/9. Cautionary Tales.vtt 3.0 kB
  • 5. How to apply Machine Learning for Data Science/6. Data Science using SQL.vtt 2.9 kB
  • 4. The Machine Learning Process/2. 5 Step Machine Learning Process Overview.vtt 2.8 kB
  • 2. Core Concepts/1. Core Concepts Overview.vtt 2.7 kB
  • 4. The Machine Learning Process/1. The Machine Learning Process - Overview.vtt 2.3 kB
  • 5. How to apply Machine Learning for Data Science/8. Data Science using RapidMiner.vtt 1.9 kB
  • 1. Introduction/3. Thank you for investing in this Course!.vtt 1.5 kB
  • 5. How to apply Machine Learning for Data Science/2. Where to begin your journey.vtt 1.5 kB
  • 2. Core Concepts/2. Computer Science - the `Train Wreck' Definition.vtt 1.4 kB
  • 1. Introduction/2. A special message for hard of hearing and ESL students.vtt 1.3 kB
  • 6. Conclusion/1. All done! What's next.vtt 1.2 kB
  • 3. Impacts, Importance and examples/1. Impacts, Importance and examples - Overview.vtt 1.1 kB
  • 5. How to apply Machine Learning for Data Science/1. How to apply Machine Learning for Data Science - Overview.vtt 897 Bytes
  • 2. Core Concepts/5. Structured and Unstructured Data.html 139 Bytes
  • 2. Core Concepts/8. Big Data - Quiz.html 139 Bytes
  • 4. The Machine Learning Process/8. Machine Learning - Process.html 139 Bytes
  • [FreeCourseLab.com].url 126 Bytes

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