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Start Your Free Trial Today >>Build a solid foundation in Machine Learning: Linear Regression, Logistic Regression and K-Means Clustering in Python
Do you want to learn Machine Learning but donāt know where to start?
Have you been looking for a beginner-friendly course that will equip you with powerful tools for your career?
Youāve 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, Iām 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, weāve 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:
Regression:
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.Classification:
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!Clustering:
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.
Why Choose This Course?
Expert Knowledge: Learn from industry leaders with extensive experience in ML and AI.
Hands-On Learning: Engage with practical exercises and real-world case studies to apply your knowledge.
Flexibility: Whether you are starting from scratch or looking to update your skills, this course is structured to cater to your learning pace and style.
Community and Support: Join a community of like-minded learners and professionals, with access to expert support throughout your learning journey.
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!
$35
/ MonthAccelerate your Career and boost your Earning Potential with our Expert Instructors & Community! What Youāll Unlock: - š 40+ Courses (over 200 hours!) - š 17 Specialized Career Paths - š Quizzes and Practice Activities - š Certificates for Courses & Career Paths - š Prizes for Learning - š§Ŗ Weekly Live Labs (plus recordings!) - šÆ Monthly Missions to practice even more - š¼ Monthly Career Booster Events - š¬ Full access to the SDS Community - ā” Monthly Speed Networking - š„ Monthly Resume Clinics - š„ Group Mentorship Program "In just a few months of learning at SDS, I landed a Data Analyst job!" ā Sanaz Afshar, California
$157
/ MonthAccelerate your Career and boost your Earning Potential with our Expert Instructors & Community! What Youāll Unlock: - š 40+ Courses (over 200 hours!) - š 17 Specialized Career Paths - š Quizzes and Practice Activities - š Certificates for Courses & Career Paths - š Prizes for Learning - š§Ŗ Weekly Live Labs (plus recordings!) - šÆ Monthly Missions to practice even more - š¼ Monthly Career Booster Events - š¬ Full access to the SDS Community - ā” Monthly Speed Networking - š„ Monthly Resume Clinics - š„ Group Mentorship Program Plus, Pro Plan perks just for you: - š A Personalized Career Path built around your goals - š§āš« 1-on-1 Mentoring Sessions every month - āļø Personalized Resume Reviews "In just a few months of learning at SDS, I landed a Data Analyst job!" ā Sanaz Afshar, California
Course content
What is Regression?
02:14
Simple Linear Regression
02:23
Ordinary Least Squares
03:17
Multiple Linear Regression
02:26
Assumptions of Linear Regression
04:24
Linear Regression Hands-On - Step 1
04:55
Linear Regression Hands-On - Step 2
06:27
Linear Regression Hands-On - Step 3
07:17
Training Set and Test Set
02:02
Linear Regression Hands-On - Step 4
07:02
Linear Regression Hands-On - Step 5
04:58
Linear Regression Hands-On - Step 6
02:56
Linear Regression Hands-On - Step 7
03:53
Linear Regression Hands-On - Step 8
02:38
R-Squared
04:35
Adjusted R-Squared
05:30
Linear Regression Hands-On - Step 9
04:14
Linear Regression Hands-On - Step 10
03:53
Quiz: Regression
What is Classification?
02:30
Logistic Regression
04:55
Maximum Likelihood
03:51
Logistic Regression Hands-On - Step 1
06:59
Logistic Regression Hands-On - Step 2
03:21
Logistic Regression Hands-On - Step 3
05:59
Logistic Regression Hands-On - Step 4
04:22
Feature Scaling
06:27
Logistic Regression Hands-On - Step 5
07:29
Logistic Regression Hands-On - Step 6
02:41
Logistic Regression Hands-On - Step 7
01:57
Logistic Regression Hands-On - Step 8a
05:27
Logistic Regression Hands-On - Step 8b
02:42
Confusion Matrix and Accuracy
04:53
Logistic Regression Hands-On - Step 9
03:43
Logistic Regression Hands-On - Step 10
04:09
Quiz: Classification
What is Clustering?
03:20
K-Means Clustering
02:37
The Elbow Method
04:00
K-Means Clustering - Step 1
05:58
K-Means Clustering - Step 2
05:41
K-Means Clustering - Step 3a
07:20
K-Means Clustering - Step 3b
07:16
K-Means++
04:49
K-Means Clustering - Step 4
06:36
K-Means Clustering - Step 5a
06:59
K-Means Clustering - Step 5b
06:59
Quiz: Clustering