Machine Learning: Principal Component Analysis in Python
Machine Learning: Principal Component Analysis in Python, available at $59.99, has an average rating of 4.55, with 10 lectures, based on 24 reviews, and has 1639 subscribers.
You will learn about Master Principal Component Analysis in Python Become an advanced, confident, and modern data scientist from scratch Become job-ready by understanding how PCA really works behind the scenes Apply robust Machine Learning techniques for Principal Component Analysis How to think and work like a data scientist: problem-solving, researching, workflows Get fast and friendly support in the Q&A area This course is ideal for individuals who are Any people who want to start learning PCA in Machine Learning or Anyone interested in Machine Learning or Anyone who want to understand how to apply PCA in datasets using Python It is particularly useful for Any people who want to start learning PCA in Machine Learning or Anyone interested in Machine Learning or Anyone who want to understand how to apply PCA in datasets using Python.
Enroll now: Machine Learning: Principal Component Analysis in Python
Summary
Title: Machine Learning: Principal Component Analysis in Python
Price: $59.99
Average Rating: 4.55
Number of Lectures: 10
Number of Published Lectures: 8
Number of Curriculum Items: 10
Number of Published Curriculum Objects: 8
Original Price: $19.99
Quality Status: approved
Status: Live
What You Will Learn
- Master Principal Component Analysis in Python
- Become an advanced, confident, and modern data scientist from scratch
- Become job-ready by understanding how PCA really works behind the scenes
- Apply robust Machine Learning techniques for Principal Component Analysis
- How to think and work like a data scientist: problem-solving, researching, workflows
- Get fast and friendly support in the Q&A area
Who Should Attend
- Any people who want to start learning PCA in Machine Learning
- Anyone interested in Machine Learning
- Anyone who want to understand how to apply PCA in datasets using Python
Target Audiences
- Any people who want to start learning PCA in Machine Learning
- Anyone interested in Machine Learning
- Anyone who want to understand how to apply PCA in datasets using Python
You’ve just stumbled upon the most complete, in-depth Principal Component Analysis course online.
Whether you want to:
– build the skills you need to get your first data science job
– move to a more senior software developer position
– become a computer scientist mastering in data science
– or just learn PCA to be able to create your own projects quickly.
…this complete Principal Component Analysis Masterclass is the course you need to do all of this, and more.
This course is designed to give you the PCA skills you need to become a data science expert. By the end of the course, you will understand the PCA technique extremely well and be able to apply it in your own data science projects and be productive as a computer scientist and developer.
What makes this course a bestseller?
Like you, thousands of others were frustrated and fed up with fragmented Youtube tutorials or incomplete or outdated courses which assume you already know a bunch of stuff, as well as thick, college-like textbooks able to send even the most caffeine-fuelled coder to sleep.
Like you, they were tired of low-quality lessons, poorly explained topics, and confusing info presented in the wrong way. That’s why so many find success in this complete Principal Component Analysis course. It’s designed with simplicity and seamless progression in mind through its content.
This course assumes no previous data science experience and takes you from absolute beginner core concepts. You will learn the core dimensionality reduction skills and master the PCA technique. It’s a one-stop shop to learn PCA. If you want to go beyond the core content you can do so at any time.
What if I have questions?
As if this course wasn’t complete enough, I offer full support, answering any questions you have.
This means you’ll never find yourself stuck on one lesson for days on end. With my hand-holding guidance, you’ll progress smoothly through this course without any major roadblocks.
There’s no risk either!
This course comes with a guarantee. Meaning if you are not completely satisfied with the course or your progress, simply let me know and I’ll refund you 100%, every last penny no questions asked.
You either end up with Haskell skills, go on to develop great programs and potentially make an awesome career for yourself, or you try the course and simply get all your money back if you don’t like it…
You literally can’t lose.
Moreover, the course is packed with practical exercises that are based on real-life case studies. So not only will you learn the theory, but you will also get lots of hands-on practice building your own models.
And as a bonus, this course includes Python code templateswhich you can download and use on your own projects.
Ready to get started, developer?
Enroll nowusing the “Add to Cart” button on the right, and get started on your way to creative, advanced PCA brilliance. Or, take this course for a free spin using the preview feature, so you know you’re 100% certain this course is for you.
See you on the inside (hurry, PCA is waiting!)
Course Curriculum
Chapter 1: Code Environment Setup
Lecture 1: Google Colab for Programming in Python
Chapter 2: Principal Component Analysis (PCA)
Lecture 1: Introduction to PCA
Lecture 2: Introduction to the Dataset
Lecture 3: Initial Visualization
Lecture 4: Using PCA
Chapter 3: Final Data Science Project – Images
Lecture 1: Images
Lecture 2: Introduction to Image Dataset
Lecture 3: Principal Component Analysis
Instructors
-
Lucas Bazilio
Engineer and Mathematician
Rating Distribution
- 1 stars: 0 votes
- 2 stars: 0 votes
- 3 stars: 3 votes
- 4 stars: 4 votes
- 5 stars: 17 votes
Frequently Asked Questions
How long do I have access to the course materials?
You can view and review the lecture materials indefinitely, like an on-demand channel.
Can I take my courses with me wherever I go?
Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!
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