Machine learning is one of the most sought–after skills in the market giving you powerful insights into data. Today, implementations of Machine Learning are adopted throughout Industry and its concepts are many. Python makes this easier with its huge set of libraries that can be used for Machine Learning. The effective blend of Machine Learning with Python helps in implementing solutions to real–world problems as well as automating analytical model.
This comprehensive 4–in–1 course follows a step–by–step practical approach to building powerful Machine Learning models using Python. Initially, you’ll use pre–written libraries in python to work with powerful algorithms and get an intuitive understanding of where to use which machine learning approach. You’ll explore Tips and tricks to speed up your modeling process and obtain better results. Moving further, you’ll learn modern techniques for solving supervised learning problems. Finally, you’ll eliminate common data wrangling problems in Pandas and scikit–learn as well as perform common natural language processing featuring engineering tasks.
By the end of the course, you’ll explore practical and unique solutions to common Machine Learning problems to avoid any roadblocks while working with the Python data science ecosystem.
Contents and Overview
This training program includes 4 complete courses, carefully chosen to give you the most comprehensive training possible.
Courses : 212
Specification: Python Machine Learning: Projects, Tips and Troubleshooting
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