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:
Python String isidentifier()
Python Set intersection()
Deep Learning for Natural Language Processing - Palash Goyal & Sumit Pandey & Karan Jain
Python Data Types
Python break and continue
Python Program to Parse a String to a Float or Int
Python Program to Check If Two Strings are Anagram
Java Deep Learning Essentials - Yusuke Sugomori
Python Set issuperset()
Python pass statement
Python Program to Create a Long Multiline String
Python Dictionary values()
Python Set difference_update()
Natural Language Processing with Python - Steven Bird & Ewan Klein & Edward Loper
Deep Learning with Theano - Christopher Bourez
Python list()
Python vars()
How to Get Started With Python?
Python String isalnum()
Python isinstance()
Natural Language Processing Recipes - Akshay Kulkni & Adarsha Shivananda
Deep Learning from Scratch - Building with Python form First Principles - Seth Weidman
Python len()
Python sorted()
Introduction to Deep Learning - Eugene Charniak
Deep Learning with Python - A Hands-on Introduction - Nikhil Ketkar
Python Program to Split a List Into Evenly Sized Chunks
Python Deeper Insights into Machine Learning - Sebastian Raschka & David Julian & John Hearty
Python classmethod()
Machine Learning with spark and python - Michael Bowles
Python Closures
Python Sets
