Deep Learning Prerequisites The Numpy Stack in Python

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Deep Learning Prerequisites The Numpy Stack in Python的二维码

文档列表

6. Appendix FAQ/3. Windows-Focused Environment Setup 2018.mp4 195.3 MB
6. Appendix FAQ/6. Proof that using Jupyter Notebook is the same as not using it.mp4 82.1 MB
6. Appendix FAQ/4. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 46.1 MB
6. Appendix FAQ/8. What order should I take your courses in (part 2).mp4 39.4 MB
6. Appendix FAQ/2. Bonus Section on Machine Learning Basics.mp4 36.7 MB
3. Pandas/7. .values vs .as_matrix().mp4 34.9 MB
6. Appendix FAQ/7. What order should I take your courses in (part 1).mp4 30.7 MB
6. Appendix FAQ/5. Python 2 vs Python 3.mp4 20.0 MB
6. Appendix FAQ/1. Exercises.mp4 17.5 MB
4. Matplotlib/4. Plotting Images.mp4 12.8 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 7.9 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 FAQ/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 FAQ/8. What order should I take your courses in (part 2).srt 23.6 kB
6. Appendix FAQ/3. Windows-Focused Environment Setup 2018.srt 20.6 kB
6. Appendix FAQ/7. What order should I take your courses in (part 1).srt 16.4 kB
6. Appendix FAQ/4. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.srt 14.8 kB
6. Appendix FAQ/6. Proof that using Jupyter Notebook is the same as not using it.srt 14.5 kB
6. Appendix FAQ/1. Exercises.srt 10.7 kB
3. Pandas/7. .values vs .as_matrix().srt 9.0 kB
6. Appendix FAQ/2. Bonus Section on Machine Learning Basics.srt 8.7 kB
1. Introduction and Outline/1. What’s this course about How can you succeed What should you know first.srt 8.4 kB
2. Numpy/7. More Matrix Operations.srt 7.9 kB
2. Numpy/1. Lists vs. Arrays.srt 7.7 kB
5. Scipy/5. Other Interesting Scipy Functions.srt 6.6 kB
6. Appendix FAQ/5. Python 2 vs Python 3.srt 6.2 kB
5. Scipy/1. Gaussian PDF and CDF.srt 6.1 kB
3. Pandas/1. Manual Data Loading.srt 5.8 kB
2. Numpy/2. Dot product 1 For loop vs. cosine method vs. dot function.srt 5.7 kB
4. Matplotlib/4. Plotting Images.srt 5.6 kB
3. Pandas/3. More about DataFrames Selecting Rows and Columns.srt 5.5 kB
1. Introduction and Outline/2. Where to get the code (and how to install libraries).srt 5.0 kB
2. Numpy/4. Vectors and Matrices.srt 4.8 kB
3. Pandas/2. DataFrames.srt 4.4 kB
2. Numpy/5. Generating Matrices to Work With.srt 3.9 kB
4. Matplotlib/1. Line Chart.srt 3.6 kB
6. Appendix FAQ/9. Where to get Udemy coupons and FREE deep learning material.srt 3.5 kB
4. Matplotlib/2. Scatterplot.srt 3.5 kB
3. Pandas/4. Even More about DataFrames Column Names.srt 3.4 kB
2. Numpy/6. Matrix Products.srt 3.3 kB
4. Matplotlib/3. Histogram.srt 3.3 kB
3. Pandas/5. The apply() Function.srt 3.3 kB
5. Scipy/3. Sampling from a Gaussian Distribution (Spherical and Axis-aligned Elliptical).srt 3.0 kB
2. Numpy/8. Solving a Linear System.srt 2.9 kB
5. Scipy/4. Sampling from a General Multivariate Normal.srt 2.8 kB
3. Pandas/6. Joins.srt 2.4 kB
5. Scipy/2. Sampling from a Gaussian Distribution (1-D).srt 1.7 kB
2. Numpy/9. Word Problem.srt 1.7 kB
2. Numpy/3. Dot product 2 Speed comparison.srt 1.6 kB
1. Introduction and Outline/4. Python 2 or Python 3.srt 1.5 kB
1. Introduction and Outline/3. How will you practice what you've learned in this course.html 163 Bytes

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