Machine Learning Real World projects in Python

Build a Portfolio of Machine Learning projects with Python, Regression algos , Unsupervised Machine Learning & More!

What you'll learn:
Machine Learning Engineers earn on average $164,000 - become Job Ready ML Engineer with this course!
Go from zero to hero in Entire Pipeline of Machine learning from Data Collection to building a Machine Learning Model
Solve any problem in your business, job or in real-time with powerful Machine Learning algorithms
Mathematics behind All Machine Learning algos ( Linear Regression , logistic , Decision Tree , Ensemble algos , KNN , Naive Bayes & many more !
Various Feature selection Techniques & how to apply it in Real-World
How to Approach a problem in Real-world..
Case studies
Requirements:
Basic knowledge of Python programming is recommended.
Description:
Machine Learning is one of the hottest technology field in the world right now! This field is exploding with opportunities and career prospects. Machine Learning techniques are widely used in several sectors now a days such as banking, healthcare, finance, education transportation and technology.

This course covers several technique in a practical manner, the projects include coding sessions as well as Algorithm Intuition:So, if you’ve ever wanted to play a role in the future of technology development, then here’s your chance to get started with Machine Learning. Because in a practical life, machine learning seems to be complex and tough,thats why we’ve designed a course to help break it down into real world use-cases that are easier to understand.
1.Task #1 @Predicting the Hotel booking  : Predict Whether booking  is going to cancel or not
3.Task #2 @Predict Whether Person has a Chronic Disease or not: Develop a Machine learning  Model that predicts whether person has kidney disease or not
2.Task #3 @Predict the Prices of Flight: Predict the prices of Flght using Regression & Ensemble Algorithms..


The course covers a number of different machine learning algorithms such as Regression and Classification algorithms. From there you will learn how to incorporate these algorithms into actual projects so you can see how they work in action! But, that’s not all. In addition to quizzes that you’ll find at the end of each section, the course also includes a 3 brand new projects that can help you experience the power of Machine Learning using real-world examples!

Who this course is for:
Data Scientists who want to apply their knowledge on Real World Case Studies
Machine Learning Enthusiasts who look to add more projects to their Portfolio

More Info