AI and ML in Python on Linux

- The Python Environment for AI and ML on Linux

In the era of big data and artificial intelligence (AI), data science and machine learning (ML) have become key to many fields of science and technology. 

An essential aspect of working with data is the ability to describe, summarize and represent the data visually. Python statistics libraries are comprehensive, popular, and widely used tools that will assist you in working with data. 

Choose Linux as your operating system - Python, the undisputed king among languages ​​for ML, runs best in Linux and all dependencies can be easily installed. The situation is similar for other popular languages ​​R and Octave. Tensorflow has become one of the most powerful deep learning toolkits and works best on Linux.

Use adequate hardware to train the model - Training a model typically requires a heavy-duty system that includes high memory (RAM), graphics card, and processor. Using lower-end hardware may take more time to train, and your system may hang and overheat.

- Resources of Python TensorFlow Tutorial Websites

Here are some of the best Python tutorial websites:

• Real Python (https://realpython.com/): A great website for learning Python for beginners and experienced programmers alike. It has a wide range of tutorials, articles, and projects that will help you master the language. 
• Learn Python: A tutorial from Codecademy that teaches you the basics of Python in an interactive way. It's a great resource for beginners who want to learn by doing.
• The TensorFlow tutorials: The TensorFlow tutorials are written as Jupyter notebooks and run directly in Google Colab - a hosted notebook environment that requires no setup. At the top of each tutorial, you'll see a Run in Google Colab button. Click the button to open the notebook and run the code yourself.

These are just a few of the many great Python tutorial websites out there. With so many resources available, there's no excuse not to learn Python today!