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Your Guide to Getting Ahead with Python!
Today, several commercial apps and research projects make use of machine learning, but this field is not only meant for big companies with extensive research teams, a beginner can get started, too.
Machine Learning came into prominence in the 1990s, when researchers and scientists started highlighting it as a sub-field of Artificial Intelligence (AI), detailing how such techniques borrow concepts from AI, probability, and statistics, which perform far better when compared to fixed rule-based models requiring a lot of manual time and effort.
Of course, as we have pointed out earlier, Machine Learning didn’t just come out of nowhere in the 1990s. It is a multi-disciplinary field that has gradually evolved over time and is still evolving as we speak.
Meanwhile, Python is growing and becoming a dominant platform to use with machine learning. The primary reason for adopting Python is because it is a general purpose programming language which can be used both for R&D and in production.
Python Machine Learning for Beginners dives into the basics of machine learning using an approachable, well-known programming language, Python.
In this guide, we will review the purpose of Machine Learning and where it applies to the real world and will also cover popular Machine Learning topics, such as supervised vs unsupervised learning, model evaluation, and Machine Learning algorithms