This book focuses on a speci fic sub- field of machine learning called predictive modeling. This is the field of machine learning that is the most useful in industry and the type of machine learning that the scikit-learn library in Python excels at facilitating. Unlike statistics, where models are used to understand data, predictive modeling is laser focused on developing models that make the most accurate predictions at the expense of explaining why predictions are made. Unlike the broader field of machine learning that could feasibly be used with data in any format, predictive modeling is primarily focused on tabular data (e.g. tables of numbers like in a spreadsheet).
Related posts:
Scikit-learn Cookbook Second Edition over 80 recipes for machine learning - Julian Avila & Trent Hau...
Python zip()
Python Dictionary popitem()
Python isinstance()
Python Program to Print all Prime Numbers in an Interval
Deep Learning with PyTorch - Vishnu Subramanian
Python Functions
Python 3 for Absolute Beginners - Tim Hall & J.P Stacey
Python Dictionary values()
Python String rfind()
Python String swapcase()
Python Program to Print Output Without a Newline
Python *args and **kwargs
Python Program to Find the Sum of Natural Numbers
APIs in Node.js vs Python - A Comparison
Python id()
Python Program to Iterate Over Dictionaries Using for Loop
Python Set add()
Python Program to Find HCF or GCD
Python Dictionary copy()
Python Set union()
Python Program to Create a Countdown Timer
Introduction to Deep Learning Business Application for Developers - Armando Vieira & Bernardete Ribe...
Python String split()
Python Get Current time
Python Tuple
Python List insert()
Python List reverse()
Python Strings
Python Machine Learning Second Edition - Sebastian Raschka & Vahid Mirjalili
Python setattr()
Python chr()