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[Udemy] Python Programming Machine Learning, Deep Learning (05.2021)

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[Udemy] Python Programming Machine Learning, Deep Learning (05.2021)

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种子哈希:ccfae7bd35a8f128dc08a7e992ff0cf153d97987
文件大小: 2.81G
已经下载:7016次
下载速度:极快
收录时间:2022-03-19
最近下载:2025-08-09

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文件列表

  • 11. Projects/2. Project - 2.mp4 177.5 MB
  • 6. Machine Learning/15. Choosing the right algorithm and model.mp4 155.7 MB
  • 5. Numpy Library/8. Using Numpy in Linear Algebra.mp4 117.6 MB
  • 11. Projects/1. Project - 1.mp4 106.5 MB
  • 6. Machine Learning/12. Unsupervised Machine Learning Methods.mp4 92.2 MB
  • 10. Transfer Learning/1. What is Transfer Learning.mp4 89.5 MB
  • 6. Machine Learning/16. Training and testing the model.mp4 88.1 MB
  • 11. Projects/3. Project - 3.mp4 86.3 MB
  • 7. Artificial Neural Network/3. Creating a Simple ANN.mp4 83.3 MB
  • 5. Numpy Library/5. Numpy Functions.mp4 82.3 MB
  • 5. Numpy Library/7. Numpy Exercises.mp4 77.8 MB
  • 8. Convolutional Neural Network (CNN)/1. What is CNN.mp4 75.9 MB
  • 11. Projects/4. Project - 4.mp4 75.8 MB
  • 6. Machine Learning/11. Supervised Machine Learning Methods - 4.mp4 73.7 MB
  • 3. Fundamentals of Python/5. Lists, Tuples, Dictionaries and Sets.mp4 69.6 MB
  • 7. Artificial Neural Network/8. What is TensorFlow.mp4 65.6 MB
  • 7. Artificial Neural Network/4. Tensor Operations.mp4 65.1 MB
  • 4. Object Oriented Programming/5. Overriding and Overloading.mp4 61.7 MB
  • 6. Machine Learning/10. Supervised Machine Learning Methods - 3.mp4 58.8 MB
  • 6. Machine Learning/9. Supervised Machine Learning Methods - 2.mp4 58.1 MB
  • 9. Recurrent Neural Network and LTSM/1. Understanding RNN and LSTM Networks.mp4 53.3 MB
  • 3. Fundamentals of Python/4. Loops.mp4 51.5 MB
  • 5. Numpy Library/3. Array and features.mp4 50.2 MB
  • 3. Fundamentals of Python/10. Exercise Solution.mp4 50.0 MB
  • 6. Machine Learning/7. Machine Learning Methods.mp4 47.8 MB
  • 7. Artificial Neural Network/7. Optimizers.mp4 44.4 MB
  • 7. Artificial Neural Network/2. Anatomy of Neural Network.mp4 44.4 MB
  • 5. Numpy Library/9. NumExpr Guide.mp4 44.2 MB
  • 3. Fundamentals of Python/1. Data Types in Python.mp4 43.1 MB
  • 6. Machine Learning/3. Turing Machine and Turing Test.mp4 42.9 MB
  • 3. Fundamentals of Python/6. Data Type Operators and Methods.mp4 42.4 MB
  • 5. Numpy Library/6. Indexing and Slicing.mp4 42.4 MB
  • 2. Python Setup/1. Installing Anaconda Distribution and Python.mp4 39.4 MB
  • 6. Machine Learning/5. Learning representations from data.mp4 36.6 MB
  • 3. Fundamentals of Python/3. Conditionals.mp4 36.3 MB
  • 4. Object Oriented Programming/2. Constructor.mp4 35.5 MB
  • 4. Object Oriented Programming/4. Inheritance.mp4 34.2 MB
  • 6. Machine Learning/6. Workflow of Machine Learning.mp4 33.2 MB
  • 6. Machine Learning/8. Supervised Machine Learning Methods - 1.mp4 32.5 MB
  • 7. Artificial Neural Network/5. Tensor Operations 2.mp4 31.2 MB
  • 3. Fundamentals of Python/2. Operators in Python.mp4 31.1 MB
  • 5. Numpy Library/1. What is Numpy.mp4 28.0 MB
  • 3. Fundamentals of Python/8. Functions in Python.mp4 27.3 MB
  • 6. Machine Learning/14. Data pre-processing.mp4 27.2 MB
  • 2. Python Setup/2. Overview of Jupyter Notebook and Google Colab.mp4 26.6 MB
  • 6. Machine Learning/17. Evaluation.mp4 25.6 MB
  • 6. Machine Learning/2. History of Machine Learning.mp4 25.0 MB
  • 4. Object Oriented Programming/3. Methods.mp4 24.8 MB
  • 7. Artificial Neural Network/6. Keras API.mp4 24.4 MB
  • 7. Artificial Neural Network/1. What is Artificial Neural Network (ANN).mp4 24.1 MB
  • 3. Fundamentals of Python/7. Modules in Python.mp4 22.1 MB
  • 6. Machine Learning/4. What is Deep Learning.mp4 21.5 MB
  • 6. Machine Learning/13. Gathering data.mp4 18.5 MB
  • 5. Numpy Library/4. Array’s Operators.mp4 18.4 MB
  • 4. Object Oriented Programming/1. Logic of OOP.mp4 17.2 MB
  • 6. Machine Learning/1. AI, Machine Learning and Deep Learning.mp4 17.0 MB
  • 1. Intro to Deep Learning with Python/1. Introduction to Deep Learning with Python.mp4 15.2 MB
  • 5. Numpy Library/2. Why Numpy.mp4 14.3 MB
  • 3. Fundamentals of Python/9. Exercise Analyse.mp4 6.0 MB
  • 5. Numpy Library/8. Using Numpy in Linear Algebra.srt 31.3 kB
  • 6. Machine Learning/12. Unsupervised Machine Learning Methods.srt 27.2 kB
  • 11. Projects/2. Project - 2.srt 21.3 kB
  • 7. Artificial Neural Network/8. What is TensorFlow.srt 20.5 kB
  • 11. Projects/1. Project - 1.srt 20.5 kB
  • 5. Numpy Library/5. Numpy Functions.srt 19.5 kB
  • 6. Machine Learning/11. Supervised Machine Learning Methods - 4.srt 19.2 kB
  • 10. Transfer Learning/1. What is Transfer Learning.srt 19.2 kB
  • 3. Fundamentals of Python/5. Lists, Tuples, Dictionaries and Sets.srt 17.9 kB
  • 8. Convolutional Neural Network (CNN)/1. What is CNN.srt 17.6 kB
  • 6. Machine Learning/7. Machine Learning Methods.srt 16.4 kB
  • 6. Machine Learning/10. Supervised Machine Learning Methods - 3.srt 16.2 kB
  • 6. Machine Learning/9. Supervised Machine Learning Methods - 2.srt 15.6 kB
  • 11. Projects/3. Project - 3.srt 15.3 kB
  • 5. Numpy Library/7. Numpy Exercises.srt 15.0 kB
  • 9. Recurrent Neural Network and LTSM/1. Understanding RNN and LSTM Networks.srt 14.9 kB
  • 11. Projects/4. Project - 4.srt 14.9 kB
  • 7. Artificial Neural Network/3. Creating a Simple ANN.srt 14.8 kB
  • 3. Fundamentals of Python/1. Data Types in Python.srt 13.8 kB
  • 6. Machine Learning/5. Learning representations from data.srt 13.7 kB
  • 6. Machine Learning/3. Turing Machine and Turing Test.srt 13.6 kB
  • 7. Artificial Neural Network/7. Optimizers.srt 12.2 kB
  • 3. Fundamentals of Python/4. Loops.srt 12.2 kB
  • 5. Numpy Library/3. Array and features.srt 11.7 kB
  • 7. Artificial Neural Network/4. Tensor Operations.srt 11.2 kB
  • 6. Machine Learning/6. Workflow of Machine Learning.srt 11.0 kB
  • 3. Fundamentals of Python/2. Operators in Python.srt 10.9 kB
  • 6. Machine Learning/8. Supervised Machine Learning Methods - 1.srt 10.6 kB
  • 7. Artificial Neural Network/2. Anatomy of Neural Network.srt 10.6 kB
  • 3. Fundamentals of Python/3. Conditionals.srt 9.9 kB
  • 4. Object Oriented Programming/5. Overriding and Overloading.srt 9.5 kB
  • 3. Fundamentals of Python/6. Data Type Operators and Methods.srt 9.1 kB
  • 6. Machine Learning/15. Choosing the right algorithm and model.srt 9.1 kB
  • 3. Fundamentals of Python/8. Functions in Python.srt 9.1 kB
  • 5. Numpy Library/6. Indexing and Slicing.srt 8.8 kB
  • 7. Artificial Neural Network/1. What is Artificial Neural Network (ANN).srt 8.3 kB
  • 7. Artificial Neural Network/6. Keras API.srt 8.2 kB
  • 7. Artificial Neural Network/5. Tensor Operations 2.srt 8.1 kB
  • 6. Machine Learning/2. History of Machine Learning.srt 7.9 kB
  • 5. Numpy Library/9. NumExpr Guide.srt 7.9 kB
  • 6. Machine Learning/17. Evaluation.srt 7.6 kB
  • 5. Numpy Library/1. What is Numpy.srt 7.5 kB
  • 6. Machine Learning/4. What is Deep Learning.srt 7.3 kB
  • 4. Object Oriented Programming/2. Constructor.srt 7.0 kB
  • 4. Object Oriented Programming/4. Inheritance.srt 6.8 kB
  • 3. Fundamentals of Python/10. Exercise Solution.srt 6.5 kB
  • 6. Machine Learning/14. Data pre-processing.srt 6.4 kB
  • 6. Machine Learning/16. Training and testing the model.srt 6.4 kB
  • 2. Python Setup/2. Overview of Jupyter Notebook and Google Colab.srt 5.8 kB
  • 6. Machine Learning/13. Gathering data.srt 5.8 kB
  • 1. Intro to Deep Learning with Python/1. Introduction to Deep Learning with Python.srt 5.8 kB
  • 6. Machine Learning/1. AI, Machine Learning and Deep Learning.srt 5.6 kB
  • 3. Fundamentals of Python/7. Modules in Python.srt 5.4 kB
  • 4. Object Oriented Programming/1. Logic of OOP.srt 5.2 kB
  • 5. Numpy Library/2. Why Numpy.srt 5.0 kB
  • 2. Python Setup/1. Installing Anaconda Distribution and Python.srt 4.7 kB
  • 5. Numpy Library/4. Array’s Operators.srt 4.3 kB
  • 4. Object Oriented Programming/3. Methods.srt 4.2 kB
  • 3. Fundamentals of Python/9. Exercise Analyse.srt 2.2 kB

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