With the rise of
machine learning in the industry, tools that can help users quickly iterate the whole process become crucial. Python, a rising star in the field of
machine learning technology, is often the first choice to take you to success. Therefore, it is necessary to use Python as a guide for machine learning.
Introduction of
machine learning with Python
So why Python? In my experience, Python is one of the easiest programming languages to learn. Now it's time to iterate through the whole process quickly, and at the same time, data scientists don't need to understand the language in depth because they can quickly master it.
How easy is it?
for anything in the_ list:print (anything)
It's so easy. Python syntax is closely related to English (or human language, not machine language) syntax. There's no stupid curly braces in Python's syntax. I have a colleague who works in quality assurance. She is not a software engineer, but she can write production grade Python code in one day. (really!)
I'll introduce several Python based libraries in the following sections. As data analysts and data scientists, we can use their masterpieces to help us accomplish our tasks. These incredible libraries are essential tools for machine learning in Python.
NumPy
This is a very famous data analysis library. Numpy can help you from calculating the median of data distribution to processing multidimensional arrays.
Pandas
This is used to process CSV files. Of course, you also need to process some tables, view statistics, and so on. Pandas is a tool that can meet your needs.
Matplotlib
After storing the data in a data frame in pandas, you may need to do some visualization to understand more about the data. After all, a picture is worth a thousand words.
Seaborn
This is another visualization tool, but it focuses more on the visualization of statistical results, such as histograms, pie charts, graphs or correlation tables.
Scikit-Learn
This is the ultimate tool for machine learning in Python. The so-called implementation of machine learning in Python refers to this - scikit learn. Everything you need, from algorithms to upgrades, can be found here.
Tensorflow and pytoch
I won't say much about these two tools. But if you're interested in deep learning, take a look at them in detail. They're worth your time.
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