Machine learning, as we have seen, is at the heart of the data science process as it is in this step that the actual models are built. This chapter is dedicated to the ML algorithms/techniques you can use to build models and libraries that implement these algorithms. Awareness of different ML algorithms and an intuitive understanding of the underlying concepts is crucial for the success of the entire data science process. We will start with a general categorization of ...
© The Author(s), under exclusive license to APress Media, LLC, part of Springer Nature 2022
V. Raina, S. KrishnamurthyBuilding an Effective Data Science Practicehttps://doi.org/10.1007/978-1-4842-7419-4_1616. Machine Learning
Get Building an Effective Data Science Practice: A Framework to Bootstrap and Manage a Successful Data Science Practice now with the O’Reilly learning platform.
O’Reilly members experience books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers.
