Machine learning and predictive analytics are becoming one of the key strategies for unlocking growth in a challenging contemporary marketplace .It is one of the fastest growing trends in modern computing and everyone wants to get into the field of machine learning. In order to obtain sufficient recognition in this field, one must be able to understand and design a machine learning system that serves the needs of a project. The idea is to prepare a Learning Path that will help you to tackle the realworld complexities of modern machine learning with innovative and cutting-edge techniques. Also, it will give you a solid foundation in the machine learning design process, and enable you to build customized machine learning models to solve unique problems.
Python Deeper Insights into Machine Learning – Sebastian Raschka & David Julian & John Hearty
Python String zfill()
Deep Learning with Applications Using Python - Navin Kumar Manaswi
Python Program to Count the Occurrence of an Item in a List
Python String isdecimal()
Understanding Machine Learning from theory to algorithms - Shai Shalev-Shwartz & Shai Ben-David
Python List pop()
Python Package
Python Program to Convert Two Lists Into a Dictionary
Python globals()
Deep Learning with Python - Francois Chollet
Python Dictionary pop()
Python super()
Python String format()
Superintelligence - Paths, Danges, Strategies - Nick Bostrom
Python Program to Differentiate Between type() and isinstance()
Python frozenset()
Deep Learning in Python - LazyProgrammer
Python Modules
Python Program to Safely Create a Nested Directory
Python List extend()
Introduction to the Math of Neural Networks - Jeff Heaton
Python Program to Find the Factorial of a Number
Artificial Intelligence - A Very Short Introduction - Margaret A.Boden
Python String isprintable()
Building Machine Learning Systems with Python - Willi Richert & Luis Pedro Coelho
Python sorted()
APIs in Node.js vs Python - A Comparison
Python Recursion
Python Tuple count()
Python issubclass()
Python Function Arguments
Deep Learning - Ian Goodfellow & Yoshua Bengio & Aaron Courville
