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Machine Learning in Python: From Zero to Hero in 10 Hours
Machine Learning & Data Science in Python with real life projects. Source codes included.
This Course Includes
udemy
4.3 (73 reviews )
8h 7m 
english
Online - Self Paced
professional certificate
Udemy
About Machine Learning in Python: From Zero to Hero in 10 Hours
Join the most comprehensive Machine Learning Hands-on Course,
because now is the time to get started! From basic concepts about
Python Programming
,
Supervised Machine Learning, Unsupervised Machine Learning
to
Reinforcement Machine Learning, Natural Language Processing (NLP),
this course covers all you need to know to become a successful
Machine Learning Professional
!
But that's not all! Along with covering all the steps of Machine Learning functions,
this course also has
quizzes and projects
, which allow you to practice the things learned throughout the course! You'll not only learn about the concepts but also practice each of those concepts through hands-on and real-life
Projects
. And if you do get stuck, you
benefit from extremely fast and friendly support
- both via direct messaging or discussion. You have my word! With more than two decades of IT experience, I have designed this course for students and professionals who wish to master how to develop and support industry-standard Machine learning projects.
This course will be kept up-to-date to ensure you don't miss out on any changes once Machine Learning is required in your project!
Why Machine Learning?
In modern times, Machine Learning is one of the most popular (if not the most!) career choices. According to available data, Machine Learning Engineer Is The Best Job of 2019 with a
344%
growth and an average base salary of
$146,085
per year. If you are looking for a
thriving career
in
Data Analytics, Artificial Intelligence, Robotics,
this is the right time to learn Machine Learning. Don't be left out and prepare well for these opportunities. So, what are you waiting for?
Pay once, benefit a lifetime
! This is an evolving course!
Machine Learning
and future enhancements will be covered in this course. You won’t lose out on anything! Don’t lose any time,
gain an edge, and start now!
What You Will Learn?
- Hands-on explanation of every major Machine Learning techniques. .
- Model Development, Deployment and Monitoring. .
- Regression: Simple, Polynomial, and Multinomial .
- Classification: Logistic Regression, K-Nearest Neighbors (KNN), Support Vector Machine (SVM), Decision Tree, Naive Bayes .
- Ensemble Modeling: Voting Classifier, Bagging, Boosting, Stacking, Random Forest .
- Implementation of every concepts explained in the course. Source codes are made available to you for your use. .
- Data Visualization with MatPlotLib and Seaborn .
- Use train, test and Cross Validation to choose and tune data .
- Feature Engineering (Reduce Noise, Outliers) and Data Preprocessing .
- Practical examples of How to trade-off between Bias, Variance, Irreducible errors using Ensemble Learning model and Bagging, Boosting .
- Understand how to implement Machine Learning at massive scale .
- Understand math and statistics behind Machine Learning models Show moreShow less.