Beginner Machine Learning in Python + ChatGPT Bonus [2023]
What you'll learn
- Machine Learning
- The Machine Learning Process
- Regression
- Ordinary Least Squares
- Simple Linear Regression
- Splitting your data into a Training set and a Test set
- Multiple Linear Regression
- R-Squared
- Adjusted R-Squared
- Classification
- Maximum Likelihood
- Feature Scaling
- Confusion Matrix
- Accuracy
- Clustering
- K-Means Clustering
- The Elbow Method
- K-Means++
- Build Machine Learning models in Python
- Make Predictions
Requirements
- Every single line of code will be fully explained so there are no prerequisites for coding skills
- This is a foundational course, so no prior knowledge of Data Science is required
- Some high-school level mathematics knowledge is recommended but not required
- We use Google Colab for coding in Python which is very intuitive, but you can also use Jupyter or another IDE
Description
Do you want to learn Machine Learning but don’t know where to start?
Have you been looking for a beginner-friendly course that will equip you with powerful tools for your career?
You’ve come to the right place!
This is Machine Learning in Python Level 1... and we will help you get started.
My name is Kirill Eremenko, I’m a Data Science instructor with over 7 years of experience, and together with my co-instructor Hadelin de Ponteves we have taught over 2M students Worldwide.
And now, we’ve created this course to help YOU get on track with Machine Learning and start applying it in YOUR career.
This course has 3 main sections:
First, we will dive into Regression, where we will learn to predict continuous variables and we will cover foundational concepts like Simple and Multiple Linear Regression, Ordinary Least Squares, Testing your Model, R-Squared and Adjusted R-Squared.
In the second section you will master Logistic Regression, which is by far the most popular model for Classification. We will learn all about Maximum Likelihood, Feature Scaling, The Confusion Matrix, Accuracy Ratios.... and you will build your very first Logistic Regression!
The third and final section is all about Clustering. We will investigate the concepts of unsupervised learning and you will practice using K-Means Clustering to discover previously unseen patterns in your data.
Sound exciting?
Well, in this course not only will you learn the theory behind all of these Machine Learning models, but you will also practice applying them in different scenarios so that you are prepared for the Real World.
Plus, you will get Python code templates which you can download and keep. These are invaluable tools which you can apply in your own projects right away.
So, what are you waiting for?
Sign up today and take your career to the next level with Machine Learning!
Who this course is for:
- Anyone interested in Data Science
- Anyone who wants to become a Data Scientist
- Anyone interested in Machine Learning
- Anyone who wants to become a ML or AI engineer
- Data Science professionals
- Machine Learning professionals
- Anyone who wants to add Machine Learning to their CV or career toolkit
Instructors
![Hadelin de Ponteves](data:image/svg+xml,%3Csvg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 64 64"%3E%3C/svg%3E){kind=avatar}
- 4.5 Instructor Rating
- 306,597 Reviews
- 1,687,839 Students
- 43 Courses
Hadelin is an online entrepreneur who has created 30+ top-rated educational e-courses to the world on new technology topics such as Artificial Intelligence, Machine Learning, Deep Learning, Blockchain and Cryptocurrencies. He is passionate about bringing this knowledge to the world and help as much people as possible. So far more than 1.6 million students have subscribed to his courses.
- 4.5 Instructor Rating
- 617,707 Reviews
- 2,332,870 Students
- 59 Courses
My name is Kirill Eremenko and I am super-psyched that you are reading this!
Professionally, I come from the Data Science consulting space with experience in finance, retail, transport and other industries. I was trained by the best analytics mentors at Deloitte Australia and since starting on Udemy I have passed on my knowledge to thousands of aspiring data scientists.
From my courses you will straight away notice how I combine my real-life experience and academic background in Physics and Mathematics to deliver professional step-by-step coaching in the space of Data Science. One of the strongest sides of my teaching style is that I focus on intuitive explanations, so you can be sure that you will truly understand even the most complex topics.
To sum up, I am absolutely and utterly passionate about Data Science and I am looking forward to sharing my passion and knowledge with you!