[FreeCourseLab.com] Udemy - Deep Learning Prerequisites The Numpy Stack in Python

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[FreeCourseLab.com] Udemy - Deep Learning Prerequisites The Numpy Stack in Python

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种子哈希：b335180584e47c34a1567b52f3108560af50ddcb
文件大小：852.7M
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收录时间：2020-02-13
最近下载：2025-10-04

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文件列表

  • 6. Appendix/3. Windows-Focused Environment Setup 2018.vtt 195.3 MB
  • 6. Appendix/3. Windows-Focused Environment Setup 2018.mp4 195.3 MB
  • 6. Appendix/6. Proof that using Jupyter Notebook is the same as not using it.mp4 82.1 MB
  • 6. Appendix/4. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 46.0 MB
  • 6. Appendix/8. What order should I take your courses in (part 2).mp4 39.5 MB
  • 6. Appendix/2. Bonus Section on Machine Learning Basics.mp4 36.7 MB
  • 3. Pandas/7. .values vs .as_matrix().mp4 34.9 MB
  • 6. Appendix/7. What order should I take your courses in (part 1).mp4 30.8 MB
  • 6. Appendix/5. Python 2 vs Python 3.mp4 20.0 MB
  • 6. Appendix/1. Exercises.mp4 17.5 MB
  • 4. Matplotlib/4. Plotting Images.mp4 12.7 MB
  • 2. Numpy/7. More Matrix Operations.mp4 12.6 MB
  • 2. Numpy/1. Lists vs. Arrays.mp4 11.2 MB
  • 1. Introduction and Outline/1. What’s this course about How can you succeed What should you know first.mp4 10.6 MB
  • 5. Scipy/5. Other Interesting Scipy Functions.mp4 10.5 MB
  • 5. Scipy/1. Gaussian PDF and CDF.mp4 8.9 MB
  • 3. Pandas/3. More about DataFrames Selecting Rows and Columns.mp4 8.6 MB
  • 2. Numpy/2. Dot product 1 For loop vs. cosine method vs. dot function.mp4 8.6 MB
  • 3. Pandas/1. Manual Data Loading.mp4 8.5 MB
  • 1. Introduction and Outline/2. Where to get the code (and how to install libraries).mp4 7.9 MB
  • 5. Scipy/3. Sampling from a Gaussian Distribution (Spherical and Axis-aligned Elliptical).mp4 7.8 MB
  • 3. Pandas/2. DataFrames.mp4 7.3 MB
  • 4. Matplotlib/3. Histogram.mp4 6.8 MB
  • 2. Numpy/5. Generating Matrices to Work With.mp4 6.7 MB
  • 4. Matplotlib/2. Scatterplot.mp4 6.5 MB
  • 2. Numpy/4. Vectors and Matrices.mp4 6.5 MB
  • 3. Pandas/4. Even More about DataFrames Column Names.mp4 6.1 MB
  • 4. Matplotlib/1. Line Chart.mp4 5.8 MB
  • 3. Pandas/5. The apply() Function.mp4 5.7 MB
  • 5. Scipy/4. Sampling from a General Multivariate Normal.mp4 5.3 MB
  • 2. Numpy/8. Solving a Linear System.mp4 4.8 MB
  • 5. Scipy/2. Sampling from a Gaussian Distribution (1-D).mp4 4.7 MB
  • 2. Numpy/6. Matrix Products.mp4 4.6 MB
  • 3. Pandas/6. Joins.mp4 4.2 MB
  • 6. Appendix/9. Where to get Udemy coupons and FREE deep learning material.mp4 4.2 MB
  • 2. Numpy/9. Word Problem.mp4 3.5 MB
  • 2. Numpy/3. Dot product 2 Speed comparison.mp4 3.3 MB
  • 1. Introduction and Outline/4. Python 2 or Python 3.mp4 1.9 MB
  • 6. Appendix/8. What order should I take your courses in (part 2).vtt 20.7 kB
  • 6. Appendix/7. What order should I take your courses in (part 1).vtt 14.4 kB
  • 6. Appendix/4. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.vtt 12.7 kB
  • 6. Appendix/6. Proof that using Jupyter Notebook is the same as not using it.vtt 12.5 kB
  • 6. Appendix/1. Exercises.vtt 9.5 kB
  • 3. Pandas/7. .values vs .as_matrix().vtt 7.9 kB
  • 6. Appendix/2. Bonus Section on Machine Learning Basics.vtt 7.6 kB
  • 1. Introduction and Outline/1. What’s this course about How can you succeed What should you know first.vtt 7.4 kB
  • 2. Numpy/7. More Matrix Operations.vtt 6.8 kB
  • 2. Numpy/1. Lists vs. Arrays.vtt 6.6 kB
  • 5. Scipy/5. Other Interesting Scipy Functions.vtt 5.7 kB
  • 6. Appendix/5. Python 2 vs Python 3.vtt 5.5 kB
  • 5. Scipy/1. Gaussian PDF and CDF.vtt 5.4 kB
  • 3. Pandas/1. Manual Data Loading.vtt 5.1 kB
  • 2. Numpy/2. Dot product 1 For loop vs. cosine method vs. dot function.vtt 5.0 kB
  • 4. Matplotlib/4. Plotting Images.vtt 4.9 kB
  • 3. Pandas/3. More about DataFrames Selecting Rows and Columns.vtt 4.7 kB
  • 1. Introduction and Outline/2. Where to get the code (and how to install libraries).vtt 4.5 kB
  • 2. Numpy/4. Vectors and Matrices.vtt 4.2 kB
  • 3. Pandas/2. DataFrames.vtt 3.9 kB
  • 2. Numpy/5. Generating Matrices to Work With.vtt 3.4 kB
  • 4. Matplotlib/1. Line Chart.vtt 3.1 kB
  • 6. Appendix/9. Where to get Udemy coupons and FREE deep learning material.vtt 3.1 kB
  • 3. Pandas/4. Even More about DataFrames Column Names.vtt 3.0 kB
  • 4. Matplotlib/2. Scatterplot.vtt 3.0 kB
  • 2. Numpy/6. Matrix Products.vtt 3.0 kB
  • 3. Pandas/5. The apply() Function.vtt 2.9 kB
  • 4. Matplotlib/3. Histogram.vtt 2.9 kB
  • 5. Scipy/3. Sampling from a Gaussian Distribution (Spherical and Axis-aligned Elliptical).vtt 2.6 kB
  • 2. Numpy/8. Solving a Linear System.vtt 2.6 kB
  • 5. Scipy/4. Sampling from a General Multivariate Normal.vtt 2.5 kB
  • 3. Pandas/6. Joins.vtt 2.1 kB
  • 5. Scipy/2. Sampling from a Gaussian Distribution (1-D).vtt 1.5 kB
  • 2. Numpy/9. Word Problem.vtt 1.5 kB
  • 2. Numpy/3. Dot product 2 Speed comparison.vtt 1.4 kB
  • 1. Introduction and Outline/4. Python 2 or Python 3.vtt 1.4 kB
  • 1. Introduction and Outline/3. How will you practice what you've learned in this course.html 159 Bytes
  • [FreeCourseLab.com].url 126 Bytes

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