Getting Started with Scikit-Learn: A Beginner's Guide to ML
Getting Started with Scikit-Learn: A Beginner's Guide to ML, available at $39.99, has an average rating of 5, with 7 lectures, 6 quizzes, based on 1 reviews, and has 8 subscribers.
You will learn about Fundamental concepts of Machine Learning and its various types. Hands-on knowledge of various Machine Learning algorithms using the Scikit-Learn library. Techniques to pre-process data, select the right model, train, test, and evaluate Machine Learning models. Practical understanding of how to use Scikit-Learn for regression, classification, clustering, and dimensionality reduction tasks. Model evaluation techniques and the understanding of underfitting and overfitting. This course is ideal for individuals who are Beginners who are interested in Machine Learning and want to understand it through practical applications. or Python programmers who are interested in Machine Learning and want to learn how to implement Machine Learning algorithms using Scikit-Learn. or Data analysts or data scientists who want to upgrade their skills by learning Machine Learning techniques. or Anyone who is curious about how Machine Learning models work and how they can be implemented using Scikit-Learn. It is particularly useful for Beginners who are interested in Machine Learning and want to understand it through practical applications. or Python programmers who are interested in Machine Learning and want to learn how to implement Machine Learning algorithms using Scikit-Learn. or Data analysts or data scientists who want to upgrade their skills by learning Machine Learning techniques. or Anyone who is curious about how Machine Learning models work and how they can be implemented using Scikit-Learn.
Enroll now: Getting Started with Scikit-Learn: A Beginner's Guide to ML
Summary
Title: Getting Started with Scikit-Learn: A Beginner's Guide to ML
Price: $39.99
Average Rating: 5
Number of Lectures: 7
Number of Quizzes: 6
Number of Published Lectures: 7
Number of Published Quizzes: 6
Number of Curriculum Items: 13
Number of Published Curriculum Objects: 13
Original Price: ₹999
Quality Status: approved
Status: Live
What You Will Learn
- Fundamental concepts of Machine Learning and its various types.
- Hands-on knowledge of various Machine Learning algorithms using the Scikit-Learn library.
- Techniques to pre-process data, select the right model, train, test, and evaluate Machine Learning models.
- Practical understanding of how to use Scikit-Learn for regression, classification, clustering, and dimensionality reduction tasks.
- Model evaluation techniques and the understanding of underfitting and overfitting.
Who Should Attend
- Beginners who are interested in Machine Learning and want to understand it through practical applications.
- Python programmers who are interested in Machine Learning and want to learn how to implement Machine Learning algorithms using Scikit-Learn.
- Data analysts or data scientists who want to upgrade their skills by learning Machine Learning techniques.
- Anyone who is curious about how Machine Learning models work and how they can be implemented using Scikit-Learn.
Target Audiences
- Beginners who are interested in Machine Learning and want to understand it through practical applications.
- Python programmers who are interested in Machine Learning and want to learn how to implement Machine Learning algorithms using Scikit-Learn.
- Data analysts or data scientists who want to upgrade their skills by learning Machine Learning techniques.
- Anyone who is curious about how Machine Learning models work and how they can be implemented using Scikit-Learn.
Welcome to the world of machine learning!
Are you ready to unlock the potential of machine learning?
This comprehensive course is designed to provide beginners with a solid foundation in machine learning using Scikit-Learn, one of the most popular and powerful machine learning libraries in Python. Whether you’re a programming enthusiast, a data analyst, or a professional looking to expand your skill set, this course will equip you with the knowledge and practical skills to confidently dive into the world of machine learning.
Throughout this course, you will learn the fundamental concepts and techniques of machine learning, including data preprocessing, model training, and evaluation. You will gain hands-on experience in building different machine learning algorithms, such as linear regression, logistic regression, decision trees, random forests, and K-nearest neighbors, to solve real-world problems. You will engage in practical exercises, quizzes and coding examples that allow you to implement machine learning algorithms using Scikit-Learn.
By the end of this course, you will have a strong foundation in machine learning and the ability to apply Scikit-Learn effectively to solve various real-world problems. Whether you’re looking to kickstart a career in data science or simply gain practical skills in machine learning, this course is the perfect starting point for your journey into the exciting field of machine learning with Scikit-Learn.
Course Curriculum
Chapter 1: Introduction
Lecture 1: Introduction
Chapter 2: Simple Linear Regression
Lecture 1: Linear Regression using Scikit-learn
Chapter 3: Multiple Linear Regression
Lecture 1: Multiple Linear Regression in Scikit-learn
Chapter 4: Logistic Regression in Scikit-learn
Lecture 1: Logistic Regression
Chapter 5: K-Nearest Neighbors in Scikit-learn
Lecture 1: K-Nearest Neighbors
Chapter 6: Decision Tree in Scikit-learn
Lecture 1: Decision Tree
Chapter 7: Random Forest in Scikit-learn
Lecture 1: Random Forest
Instructors
-
Jitendra Singh
Edtech company
Rating Distribution
- 1 stars: 0 votes
- 2 stars: 0 votes
- 3 stars: 0 votes
- 4 stars: 0 votes
- 5 stars: 1 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!
You may also like
- The Ultimate Instagram Growth Hacking Course
- Video Marketing Masterclass
- Psychology for Managers & Entrepreneurs
- Marketing 101 for Self-Published Authors
- Pinterest Marketing from A to Z for Beginners
- Complete Google Adwords For Video: Boost Your YouTube Views!
- Launch-make your business profitable and easy
- Reddit Marketing For Business
- Retargeting and Facebook Ads Retargeting made Easy & Simple
- Affiliate Success Blueprint: ChatGPT, Canva & Pinterest
- Mastering Account-Based Marketing (ABM)
- AI-Powered Email Marketing: A Complete Guide
- PR Social Media Monitoring & Dashboards for Facebook etc
- Get More Clients Facebook Marketing for Salons and Spas
- Write a Landing page Step by Step ( apply in order )
- Complete Social Media Marketing Course 2024 -32 Courses in 1
- Master Course in Sales Funnel and Landing Page Optimization
- Email Marketing. Increase Sales With Email Marketing!
- Facebook Engagement Workshop: Growth Without Facebook Ads
- Unofficial Udemy Coupon Codes and Promotional Announcements