[FreeCourseSite.com] Udemy - Modern Deep Learning in Python

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[FreeCourseSite.com] Udemy - Modern Deep Learning in Python

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种子哈希：c317a7c02cce491dc0cd33731a421b1c6acd060c
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收录时间：2021-03-08
最近下载：2025-07-31

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文件列表

  • 09 Project Facial Expression Recognition/028 Class-Based ANN in Theano.mp4 46.1 MB
  • 10 Appendix/031 How to install Numpy Scipy Matplotlib Pandas IPython Theano and TensorFlow.mp4 46.0 MB
  • 09 Project Facial Expression Recognition/029 Class-Based ANN in TensorFlow.mp4 39.2 MB
  • 07 GPU Speedup Homework and Other Misc Topics/018 Setting up a GPU Instance on Amazon Web Services.mp4 26.9 MB
  • 10 Appendix/032 How to Code by Yourself part 1.mp4 25.7 MB
  • 06 TensorFlow/017 Building a neural network in TensorFlow.mp4 25.0 MB
  • 08 Modern Regularization Techniques/023 Dropout Regularization.mp4 23.8 MB
  • 05 Theano/015 Building a neural network in Theano.mp4 22.8 MB
  • 09 Project Facial Expression Recognition/025 Facial Expression Recognition Problem Description.mp4 22.5 MB
  • 05 Theano/014 Theano Basics Variables Functions Expressions Optimization.mp4 20.3 MB
  • 06 TensorFlow/016 TensorFlow Basics Variables Functions Expressions Optimization.mp4 17.9 MB
  • 10 Appendix/033 How to Code by Yourself part 2.mp4 15.5 MB
  • 03 Momentum and adaptive learning rates/008 Code for training a neural network using momentum.mp4 15.3 MB
  • 02 Gradient Descent Full vs Batch vs Stochastic/006 Full vs Batch vs Stochastic Gradient Descent in code.mp4 14.7 MB
  • 04 Choosing Hyperparameters/012 Grid Search in Code.mp4 14.4 MB
  • 09 Project Facial Expression Recognition/027 Utilities walkthrough.mp4 14.1 MB
  • 01 Outline the MNIST dataset and Linear Logistic Regression Benchmark/004 Where to get the MNIST dataset and Establishing a Linear Benchmark.mp4 11.7 MB
  • 03 Momentum and adaptive learning rates/010 Constant learning rate vs. RMSProp in Code.mp4 11.5 MB
  • 09 Project Facial Expression Recognition/026 The class imbalance problem.mp4 10.6 MB
  • 07 GPU Speedup Homework and Other Misc Topics/022 Theano vs. TensorFlow.mp4 9.6 MB
  • 01 Outline the MNIST dataset and Linear Logistic Regression Benchmark/003 How to Succeed in this Course.mp4 9.2 MB
  • 04 Choosing Hyperparameters/013 Random Search in Code.mp4 8.3 MB
  • 07 GPU Speedup Homework and Other Misc Topics/021 How to Improve your Theano and Tensorflow Skills.mp4 7.7 MB
  • 10 Appendix/030 Manually Choosing Learning Rate and Regularization Penalty.mp4 7.4 MB
  • 08 Modern Regularization Techniques/024 Dropout Intuition.mp4 6.4 MB
  • 01 Outline the MNIST dataset and Linear Logistic Regression Benchmark/002 Where does this course fit into your deep learning studies.mp4 6.3 MB
  • 02 Gradient Descent Full vs Batch vs Stochastic/005 What are full batch and stochastic gradient descent.mp4 6.1 MB
  • 04 Choosing Hyperparameters/011 Hyperparameter Optimization Cross-validation Grid Search and Random Search.mp4 5.8 MB
  • 07 GPU Speedup Homework and Other Misc Topics/019 Can Big Data be used to Speed Up Backpropagation.mp4 5.5 MB
  • 03 Momentum and adaptive learning rates/009 Variable and adaptive learning rates.mp4 5.3 MB
  • 01 Outline the MNIST dataset and Linear Logistic Regression Benchmark/001 Outline - what did you learn previously and what will you learn in this course.mp4 4.9 MB
  • 07 GPU Speedup Homework and Other Misc Topics/020 Exercises and Concepts Still to be Covered.mp4 4.7 MB
  • 03 Momentum and adaptive learning rates/007 Momentum.mp4 3.3 MB
  • [FCS Forum].url 133 Bytes
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