RECRUITMENT_FOR_ML_JOTANG

注：本仓库专用于解决焦糖工作室招新题 8 机器学习的题目

Github link: https://github.com/syxb2/recruitment_for_ml_jotang

Usage

$ git clone https://github.com/syxb2/recruitment_for_ml_jotang.git

$ cd recruitment_for_ml_jotang

$ pip install -r requirements.txt

• 推荐使用 VScode 打开本仓库。python 解释器选择 虚拟环境 .venv
• Jupyter Note 文件（.ipynb）推荐使用 github 网页预览。

MyEnvironment

已安装的包：

• torch
• ipykernel
• scikit-learn
• pandas
• numpy
• torchvision
• matplotlib
• transformers
• timm

in ./requirements.txt

机器环境：

• MacOS Sequoia（15）

虚拟环境：

• 使用 venv 创建 python 虚拟环境。

所用编辑器：

• Visual Studio Code

$ python --version
Python 3.10.15

$ which python
./.venv/bin/python

$ pip list
Package            Version
------------------ -----------
appnope            0.1.4
asttokens          2.4.1
certifi            2024.8.30
charset-normalizer 3.4.0
comm               0.2.2
contourpy          1.3.0
cycler             0.12.1
debugpy            1.8.6
decorator          5.1.1
exceptiongroup     1.2.2
executing          2.1.0
filelock           3.16.1
fonttools          4.54.1
fsspec             2024.9.0
huggingface-hub    0.25.2
idna               3.10
ipykernel          6.29.5
ipython            8.28.0
jedi               0.19.1
Jinja2             3.1.4
joblib             1.4.2
jupyter_client     8.6.3
jupyter_core       5.7.2
kiwisolver         1.4.7
MarkupSafe         3.0.0
matplotlib         3.9.2
matplotlib-inline  0.1.7
mpmath             1.3.0
nest-asyncio       1.6.0
networkx           3.3
numpy              2.1.2
packaging          24.1
pandas             2.2.3
parso              0.8.4
pexpect            4.9.0
pillow             10.4.0
pip                24.2
platformdirs       4.3.6
prompt_toolkit     3.0.48
psutil             6.0.0
ptyprocess         0.7.0
pure_eval          0.2.3
Pygments           2.18.0
pyparsing          3.1.4
python-dateutil    2.9.0.post0
pytz               2024.2
PyYAML             6.0.2
pyzmq              26.2.0
regex              2024.9.11
requests           2.32.3
safetensors        0.4.5
scikit-learn       1.5.2
scipy              1.14.1
setuptools         74.1.2
six                1.16.0
stack-data         0.6.3
sympy              1.13.3
threadpoolctl      3.5.0
timm               1.0.11
tokenizers         0.20.1
torch              2.4.1
torchvision        0.19.1
tornado            6.4.1
tqdm               4.66.5
traitlets          5.14.3
transformers       4.45.2
typing_extensions  4.12.2
tzdata             2024.2
urllib3            2.2.3
wcwidth            0.2.13

LICENSE

The MIT License (MIT)
Copyright © 2024 Bai Jiale [email protected]

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the “Software”), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.