Due to its versatility, flexibility, and comprehensiveness, Python is the perfect fit for machine learning solutions.
The language’s open-source and high-level nature as well as its numerous libraries provide the necessary tools for anyone working with the technology, whether it’s reinforcement, supervised, or unsupervised machine learning problems they’re dealing with.
If you consider using Python for machine learning, there are tons of blogs, books, guides, and courses out there for you to develop that skill. However, navigating around them and choosing the best resource available may be a challenge.
To help you with that, we sat down with Łukasz Eckert, an expert machine learning engineer at STX Next, and prepared a list of suggestions that you may find helpful and informative. In the article, you will also find some tips on what else you can do to get more insight into the topic.
The resources recommended below will be a solid foundation for the learning process of both software developers who want to know the basics of Python for ML and those simply expanding their already rich skill set. Read on to check them out!