Are you ready to start on your path to becoming a machine learning expert? But worried the learning curve is too steep?
Well, that’s understandable. Machine learning is typically explained using complex mathematical principles. This course, however, cuts through the math and makes it easy for you to learn how machine learning algorithms work.
This course will teach you the strengths and weaknesses of today’s most preferred machine learning algorithms. You’ll also learn the best algorithm to apply in real-world situations.
But do you wonder whether it’s worthwhile to master machine learning in these uncertain times and if machine learning engineers really have a bright future?
Listen to what the most relevant experts have to say:
- “Machine learning will automate jobs that most people thought could only be done by people.” ~ Dave Waters
- “Just as electricity transformed almost everything 100 years ago, today I actually have a hard time thinking of an industry that I don’t think AI (Artificial Intelligence) will transform in the next several years.” ~ Andrew Ng
- “A breakthrough in machine learning would be worth ten Microsofts.” ~ Bill Gates
When it comes to machine learning, you have an assortment of courses and lectures to choose from. How is this course different from the others?
Getting started is the most difficult part when you start learning something new. But the well-planned step-by-step design of this course makes not only getting started easy but also makes moving forward easier.
This is how the course is designed and your learning progresses. In every new tutorial, you build on what you have already learned and move one extra step forward. You are then assigned a small task that you solve at the beginning of the next video.
You don’t need to worry if you don’t know Python. We have a course for absolute beginners in Python, as well.
This exhaustive course will enable you to use the power of machine learning to solve real-world problems in the workplace. You’ll build strong foundational knowledge first before moving on to advanced stuff. You’ll start from scratch, and finally, you’ll learn how to implement a face recognition application.
You’ll also implement several mini projects in live coding sessions in which you’ll gain a complete understanding of how to implement any machine learning project. Some errors have been built into your assigned tasks deliberately so that you learn how to find these mistakes in the code and fix them just like a beginner.
This course is designed for both beginners with some machine learning knowledge and even for those who know nothing about machine learning.
Who this course is for:
- This course is for you if you want to learn how to train your machine just like a kid
- This course is for you if you don’t know anything about machine learning but want to know it well enough so that you can implement projects based on Artificial Intelligence
- This course is for you if you are tired of machine learning courses that are too complicated and expensive
- This course is for you if you want to learn machine learning practically
- This course is for you if you want to learn machine learning from zero and become proficient in it fast
- This course is for you if you are curious to learn about the theory of machine learning and then implement it in real-world projects.
Goals
- The importance of machine learning in this era
- How to train your machine to learn
- How can your machines learn from data
- Different machine learning methods
- Regression algorithms
- Classification algorithms
- Clustering algorithms
- Data preparation
- How to deal with image/audio video and text data
- Model optimization
- How to build machine learning models from scratch
- How to build linear regression from scratch
- How to build a classifier from the very beginning
- How to implement K-mean clustering from the absolute beginning
- Overfitting and how to fix it
- Regularization and generalization
- Data snooping and cross-validation
- Performance matrices
- Dimensionality reduction
- Cross validation and learning curves
- An overview of Deep Learning
- Introduction to DNN, CNN, and RNN
- Basic mathematics for machine learning (optional)
- Implement projects from scratch
- Implement any project using machine learning tools
- Build a face recognition application
Prerequisites
- Absolutely no prior knowledge or experience needed. Only a genuine passion to be successful!
- We expect our students to have zero knowledge of machine learning.
- Admin permission to download files.
Instructors
No student enrolled.
