Common Code Frameworks and Toolkits in Machine Learning

Nowadays, writing machine learning programs does not require us to start from scratch. There are many good frameworks and many useful toolkits

1. Pytorch#

Official website pytorch.org, a framework preferred by the academic community, based on Python syntax, easy to use.

2. Tensorflow#

The official website www.tensorflow.org, a machine learning framework from Google, has built-in keras so that developers who are new to AI can get started quickly.
The official website also provides many model examples and tutorials

3. Numpy#

Numpy is a mathematical library, which is usually competent for matrix-related data expression and calculation.

To install the Numpy package, you only need to execute pip install numpy to install successfully.

4. Opencv#

Opencv provides software packages in various languages ​​for graphics-related processing, which is very easy to use.

To install Python's Opencv package, you only need to execute pip install opencv-python to install successfully.

5. Matplotlib#

Matplotlib is a commonly used library for visualizing data, which is very powerful.

6. pandas#

pandas is a library of data analysis and manipulation tools.

7. More#

There are many other tools, welcome to add

1. Pytorch
2. Tensorflow
3. Numpy
4. Opencv
5. Matplotlib
6. pandas
7. More