The Best Resources to Learn Python for Machine Learning

Python is now the de facto language of choice for machine learning. Although it is easy to learn, you can find some helpful tips that will help you get started or improve your knowledge.

This post will show you how to learn programming languages and how to get help. This post will help you:

What is the best way to learn Python for machine learning?

• What are some good resources for learning Python?
• What to do if you have questions about Python?

Let’s get started.

How to Learn Python

You can learn a language in many different ways, whether you are learning it from a natural language like English or coding languages like Python.

Baby learns a language by mimicking and listening. Slowly, once they have learned some vocabulary and patterns, they are able to make their own sentences.

However, college students who learn Latin start with grammar rules. Single and plural, indicative, subjunctive and subjunctive. This allows us to build a Latin sentence.

You can also learn Python or any other programming language by reading code from others and trying to understand it. Then you can modify the code. You can also learn the language rules and create a program yourself.

If your ultimate goal is to learn the language and create a program from scratch, the latter approach would be advantageous. The former is more efficient and will usually get you some results faster.

I recommend that you learn from examples first. To strengthen your understanding of the language, you should revisit the rules of the language from time to time. Let’s take as an example from Wikipedia.

This Python code implements a secant method to find the root of a function. You can learn Python by looking at this example. You would be able to guess define a function if you are familiar with other programming languages.

If you don’t have any prior knowledge, it might be difficult to understand the concept of variables, functions, and loops. It is best to begin with a book about programming for beginners.

Modifying the functions is another thing you may think you could do. What if, for example, we don’t use the secant method to find root? Instead, we can use Newton’s method.

It is possible to guess how to modify line 4 of the equation. Bisection method? To decide which direction to go, you will need to add a statement if f(x2)>0. The symbol ** is visible in the f_example function. This is the exponent operator, which means x to power 2. It is x2-612, or x2-612. To see the operator hierarchy, you would need to look at the language manual.

Even a brief example such as this can teach you a lot about language features. You can learn more by looking at examples.
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What to Avoid

It is a good idea to read a book if you are determined to learn Python. You can find any Python beginner’s book at your local library. Keep the larger picture of your learning goals in mind as you read. You can do some exercises while you read. Skipping pages is a good idea.

It is not the best way to learn. It is best to not get too involved in one topic as this can distract you from the larger goal of using Python to accomplish useful things. You can treat advanced topics such as object-oriented programming, multithreading, and network sockets as a later topic.

Python is a language that is separated from its compiler or interpreter. Different interpreters may behave slightly differently.

The CPython is the standard interpreter on python.org. It is also known as the reference implementation. PyPy is another popular alternative. PyPy is a common alternative to Python 2. Keep in mind, Python 2 was the original Python and there may be some Python 2 programs around.

Resources

Reading Resources

You can also use online resources if you are unable to go to the library to get a printed book. I recommend The Python Tutorial to beginners. Although it is brief, it guides you through the various aspects of Python. This gives you a glimpse of what Python can do and how it does it.

You should probably keep the Python Language Reference as well the Python Library Reference close by after the tutorial. These will be used to look up function usages and check syntax. You don’t have to know every function.
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Programming Environment

Although Python is already built-in to macOS, you might want to upgrade to a more recent version. It is not uncommon to see Windows users using Anacronda rather than installing the Python interpreter.

Google Colab is an alternative to installing the Python programming environment and an IDE. You can write Python programs in a “notebook”. Many machine learning projects are created in the Jupyter notebook because it allows us to rapidly explore various approaches to a problem, and visually verify the results.

You can also use an online shell at https://www.python.org/shell/ to try out a short snippet. You cannot save your work, which is a disadvantage to the Google Colab.

Asking for help

If you modify a code example that you have read in a book, it might break it and cause it to fail to run. This is particularly true for machine learning examples.

These include many lines of code that cover data collection, preprocessing and building a model. Validation, training, prediction, validation, validation, presentation, and finally, presentation. First, identify the lines that are causing the error in your code.

To ensure that the output is correct, you should check each step. You can also rollback your code to find out which changes introduced errors.

It is important that you make mistakes and learn from them. You will encounter errors as you learn syntax. It will be easier to understand the error message if you can make sense of it. If the error is caused by a library you are using, confirm your syntax with its documentation.

You can search the error message on the internet if you’re still confused. You can search the error message using Google. Sometimes, StackOverflow may provide better answers.
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Additional Readings

These are some tips for beginners. The Python Tutorial, as mentioned above, is a great place to start. This is especially true when Python 3.9 was released recently and new syntax were introduced. The official online tutorial is often more up-to-date than the printed book.

There are many primer level books for Python. Some short ones that I knew are:

• Python Crash Course, 2nd edition, by Eric Matthes, 2019.
• Introduction to Computation and Programming Using Python, 3rd edition, by John Guttag, 2021.

You may find it helpful to look at more examples if you are a more advanced learner. You might find a cookbook-style book helpful as it can help you learn syntax and language tricks along with the various libraries that are available to get the job done.

• Python Cookbook, 3rd edition, by David Beazley and Brian K. Jones, 2013.

Summary

This post will explain how to study Python and provide resources that can assist you in starting. While a goal-oriented approach to studying can speed up the process, it is important to put in the considerable time before you are proficient.