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Bumps [numpy](https://github.com/numpy/numpy) from 1.13.3 to 1.22.0. Release notes Sourced from numpy's releases. v1.22.0 NumPy 1.22.0 Release Notes NumPy 1.22.0 is a big release featuring the work of 153 contributors spread...

dependabot[bot]

Bumps [tensorflow-gpu](https://github.com/tensorflow/tensorflow) from 1.4.0 to 2.7.2. Release notes Sourced from tensorflow-gpu's releases. TensorFlow 2.7.2 Release 2.7.2 This releases introduces several vulnerability fixes: Fixes a code injection in saved_model_cli (CVE-2022-29216) Fixes...

dependabot[bot]

论文想引用您的代码，您的论文出处可以分享下嘛？

hellomijia

Bumps [pillow](https://github.com/python-pillow/Pillow) from 6.2.0 to 9.0.1. Release notes Sourced from pillow's releases. 9.0.1 https://pillow.readthedocs.io/en/stable/releasenotes/9.0.1.html Changes In show_file, use os.remove to remove temporary images. CVE-2022-24303 #6010 [@​radarhere, @​hugovk] Restrict builtins within...

dependabot[bot]

Iris data with Naive byes & explain with iris example

1

AnonumusArjun

SVM_example.py

1

Implementation of Support Vector Machines

ASHMITA-DE

您好， 读过您写的书，收获很大，谢谢。 有一个疑问，如题。Time.timeit利用wrapt.dectator来计算一个函数的执行时间。通常是没有问题的。但是如果是一个嵌套函数，**外层函数的计时就是：内层函数执行时间+wrapt 自身执行的时间**。如果内层函数被执行n次，那么外层函数的计时时间就多出了n*(wrapt 自身执行时间），这可能导致时间分析不准确。比如下面的例子, outer()的总时间被错误的多计时了（100000000*wrap时间）。不知道有没有办法在wrapt之间进行通讯，来扣除内部wrapt 自身的时间（不是inner函数的执行时间哈） ``` @timing.timeit() def inner(): print("inner") @timing.timeit() def outter(): for i in range(100000000): inner() print("outer") ```

wztdream

Update Bases.py. An error happened, when I run the RandomForest.py in the forth Chapter. The label should be "p" or "e" (a char), but it asked to convert to np.float32.

busyyang

Bumps [torch](https://github.com/pytorch/pytorch) from 0.2.1+a4fc05a to 1.13.1. Release notes Sourced from torch's releases. PyTorch 1.13.1 Release, small bug fix release This release is meant to fix the following issues (regressions /...

dependabot[bot]

Bumps [tensorflow-gpu](https://github.com/tensorflow/tensorflow) from 1.4.0 to 2.12.0. Release notes Sourced from tensorflow-gpu's releases. TensorFlow 2.12.0 Release 2.12.0 TensorFlow Breaking Changes Build, Compilation and Packaging Removed redundant packages tensorflow-gpu and tf-nightly-gpu. These...

dependabot[bot]