Top 10 Best YouTube channels to learn Machine Learning

Every learning doesn’t need a paid course or investment. If you are willing to learn anything, YOUTUBE is always there.

So, if I ask, “Are you trying to find a free way to learn machine learning?” One of the greatest places to begin your journey is YouTube, which offers full-length courses, real-world projects, and tutorials from leading academics and machine learning engineers.

Some of the best YouTube channels to learn Machine Learning are StatQuest, Krish Naik, and Sentdex. These channels are particularly beneficial for novices and working professionals who want to pursue careers in data science and artificial intelligence.

What does this guide contain?

• The best YouTube channels to learn Machine Learning
• Advanced courses and beginner-friendly tutorials
• Practical coding exercises with Scikit-learn, TensorFlow, and Python
• Free substitutes for costly machine learning boot camps

The value of studying machine learning

Machine learning is more than just a catchphrase; it is influencing sectors like healthcare and finance. Imagine having the ability to create algorithms that can automate procedures or forecast trends. That sounds awesome, doesn’t it?

Adopting machine learning can lead to innovative projects and exciting career opportunities. It’s like having a superpower in your skill set, too!

Role of YouTube in education

The way we consume information has been completely transformed by YouTube. The days of sitting through boring lectures and leafing through old textbooks are long gone. These days, interesting video content can teach you anything from “how to make a soufflé” to “how to become an expert in machine learning“!

With the help of visual aids and real-world examples, the platform’s selection of machine learning YouTube tutorials makes it simpler than ever to understand difficult concepts.

With so many suggested machine learning YouTube channels, students can find content that is appropriate for their skill level, whether it be advanced ML tutorials or beginner-friendly lessons. It’s similar to having a private tutor on call all the time!

An outline of the article

In this post, we’ll examine the best YouTube channels to learn machine learning. From in-depth ML courses on YouTube to engaging interactive ML lessons, we’ll cover it all. We have everything you need, whether you’re looking for free machine learning instruction or professional-led ML tutorials on YouTube!

Prepare to explore the top educational machine learning YouTube channels by grabbing your notepad or your favourite snack. Together, let’s set out on this adventure and discover machine learning’s mysteries one video at a time!

Criteria for Selecting the Best YouTube Channels

Not every YouTube channel is made equal when it comes to machine learning. Here are some crucial factors to take into account when choosing the top YouTube channels to learn machine learning to help you sort through the deluge of content.

Quality of Content

The quality of the content should be the first consideration. This entails evaluating how educational, coherent, and captivating the videos are. Good content frequently consists of:

• Explicit explanations: Ideas ought to be divided into manageable chunks.
• Applications in the real world: Seek out channels that offer real-world instances of machine learning in action.
• Visual aids: Code walkthroughs, graphs, and charts can improve comprehension.

Keep in mind that even the most complicated algorithms can be easily mastered by a channel with captivating video content!

Knowledge of the Instructor

You wouldn’t want to learn how to fly a plane from someone who only read about it in a book, would you? Likewise, look for channels with instructors who have demonstrated machine learning expertise. Look for:

• Education: Do they have a background in data science or a similar discipline?
• Experience in the industry: Have they worked for reputable companies or on related projects?
• Teaching style: Do they interact with their audience and communicate clearly?

Consider an expert-led channel as having a backstage pass to the world of machine learning, offering insights beyond what is found in textbooks!

Participation and Community Input

An active community should be fostered by a great channel. Examine elements such as:

• Comments from users: Do viewers ask questions and get answers?
• Loyal supporters: Is the channel regularly watched and has a large number of subscribers?
• User ratings: High ratings frequently suggest that students find the material engaging.

By offering more resources and assistance, a thriving community can improve your educational experience. Furthermore, who doesn’t enjoy telling other enthusiasts about their journey?

Regularity of Updates

Since the field of machine learning is always changing, it’s important to stay current. Verify the frequency of new content uploads. This is why it’s important:

• Current information: You’re getting the newest methods and trends when you see regular uploads.
• Diverse topics: A channel that posts regularly probably covers a lot of different ML topics.
• User engagement: Regular uploads encourage subscribers to stay interested and return for more!

Takeaway: The secret to effectively learning machine learning is choosing the appropriate YouTube channels. You’ll be prepared to succeed in this fascinating field if you concentrate on high-quality content, instructor expertise, community involvement, and update frequency!

1. Sentdex

• Introduction: Harrison Kinsley blends theory and real-world coding to deliver easily understood machine learning material.
• Python programming, data analysis, regression, SVM, neural networks, and practical machine learning projects were among the main subjects covered.
• What Makes This Channel Beneficial? It provides practical instructions, arranged playlists for all skill levels, and actual coding examples.

2. DeepLearningAI (Andrew Ng)

• Introduction: This channel provides succinct, interesting 2-minute videos that summarise state-of-the-art AI research.
• Recent developments in machine learning, artificial intelligence, neural networks, graphics, and generative models were among the main subjects discussed.
• What Makes This Channel Beneficial? Ideal for keeping abreast of innovations and rapidly understanding fresh findings.

3. Two Minute Papers

• Introduction: This channel provides succinct, interesting 2-minute videos that summarise state-of-the-art AI research.
• Recent developments in machine learning, artificial intelligence, neural networks, graphics, and generative models were among the main subjects discussed.
• What Makes This Channel Beneficial? Ideal for keeping abreast of innovations and rapidly understanding fresh findings.

4. Kaggle

• Introduction: For individuals interested in contests and community-led initiatives, Kaggle’s official channel is essential.
• Key Topics Covered: Project advice, expert interviews, workflow walkthroughs, and competition tutorials.
• What Makes This Channel Beneficial? It links theory and practice, making it perfect for learning from case studies in the real world.

5. 3Blue1Brown

• Introduction: This channel, which is well-known for its ability to visualise mathematics, imaginatively demonstrates the intuition underlying machine learning.
• Calculus, linear algebra, neural networks, and algorithm intuition were among the main subjects discussed.
• What Makes This Channel Beneficial? drives machine learning and aids in the mastery of mathematical concepts by visual learners.

6. Siraj Raval

• Introduction: Siraj uses lively storytelling and straightforward explanations to bring complicated machine learning concepts to life.
• ML fundamentals, deep learning, computer vision, natural language processing, coding difficulties, and AI ethics were among the main subjects discussed.
• What Makes This Channel Beneficial? It makes difficult subjects fun and approachable for all students.

7. Applied AI Course

• Overview: Emphasised practical, project-based methods for machine learning.
• Neural networks, computer vision, reinforcement learning, and project tutorials were among the main subjects covered.
• What Makes This Channel Beneficial? It places a strong emphasis on solving real-world problems to get students ready for the workforce.

8. Krish Naik

• Introduction: Krish Naik uses real-world examples to clearly explain machine learning concepts.
• NLP, computer vision, scikit-learn, TensorFlow, PyTorch, and project-based learning were among the main subjects covered.
• What Makes This Channel Beneficial? provides all skill levels with useful, real-world applications.

9. StatQuest with Josh Starmer

• Introduction: Josh Starmer breaks down statistics, which are essential to comprehending machine learning algorithms.
• Regression, decision trees, SVMs, boosting, and machine learning mathematics were among the main subjects discussed.
• What Makes This Channel Beneficial? Incredibly user-friendly for novices and perfect for strengthening algorithmic theory.

10. Data School

• Introduction: Kevin Markham walks students through every step of the process, from cleaning data to evaluating the model.
• Python, pandas, scikit-learn, model evaluation, and machine learning best practices were among the main subjects discussed.
• What Makes This Channel Beneficial? Excellent for learning the basics and getting your hands dirty with the necessary tools.

Takeaway from YouTube’s Machine Learning Resources: Whether you’re new to machine learning or want to hone your skills, these channels each provide insightful information. Explore their playlists now to begin expanding your knowledge of machine learning!

Extra Sources and Suggestions

Although the best YouTube channels to learn Machine Learning offer a great starting point, there are a ton of resources available to help you expand your knowledge and proficiency. Let’s look at some amazing extra resources that can improve your education!

Machine Learning Books to Support Video Learning

Books provide depth and insight that video tutorials occasionally overlook, making them the fine wine of education. The following must-read titles are ideal for your YouTube journey:

• Aurélien Géron’s book “Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow”: This book provides a hands-on, practical approach.
• Christopher Bishop’s book “Pattern Recognition and Machine Learning” delves deeper into the theoretical underpinnings of machine learning.
• Ian Goodfellow, Yoshua Bengio, and Aaron Courville’s book “Deep Learning” is regarded as the bible for those who are interested in deep learning.

These books present fresh concepts and approaches in machine learning, in addition to reinforcing previously learnt ideas.

Deeper Understanding Online Courses (if applicable)

Online courses can be very helpful if you’re searching for a more structured approach outside of YouTube’s informal atmosphere. The following websites provide in-depth machine learning courses:

• Coursera: Provides classes from prestigious universities, such as Stanford (the renowned Machine Learning course taught by Andrew Ng)offers AI and ML MicroMasters programs from universities such as MIT.
• Udacity: Well-known for its Nanodegree programs that emphasise useful machine learning skills.

By enrolling in these courses, you can expand your knowledge and earn certifications that will improve your resume!

Communities and Discussion Boards to Participate in

Learning machine learning doesn’t have to be an isolated endeavour. Participating in communities can lead to networking, conversation, and support opportunities. Here are a few well-known forums to think about:

• Kaggle is more than just a platform for competitions; it also boasts a vibrant community where users can exchange ideas and discuss projects.
• Reddit (r/MachineLearning): A lively forum where enthusiasts exchange articles, pose queries, and talk about current events.
• The Data Science Society is a global community dedicated to exchanging information on machine learning and data science.

By participating in these communities, you can meet people who share your passion and stay current on trends!

Your Next Steps: You’ll have a comprehensive toolkit at your disposal if you combine these resources with the best machine learning YouTube channels. Don’t be afraid to participate in communities, take online courses, or dive into books. Your understanding will be richer the more varied your resources are!

Some Advice for Making the Most of Your YouTube Learning Experience

You’ve decided to use YouTube to learn more about machine learning. A wise decision! However, how can you maximise this wealth of knowledge? Here are some useful pointers to make sure you learn and put what you learn into practice rather than just watching videos.

Establishing Learning Objectives and Benchmarks

Set some learning objectives before you press the play button. Consider it your road map to success. Here’s how to begin:

• Establish your goals: Do you want to learn the fundamentals or take on more complex ML concepts? Choosing the appropriate content is aided by knowing your ultimate objective.
• Establish benchmarks: Divide your educational path into digestible chunks. For instance, try to finish a playlist every week or one video every day.
• Monitor your progress: After each session, record your learnings in a journal or digital tool. This introspection helps you stay motivated and solidify your knowledge!

Setting specific objectives and benchmarks will help you become an expert in machine learning rather than just aimlessly browsing YouTube!

Taking Notes While Watching Videos

If you’re anything like me, you might think, “I’ll remember that!” But let’s face it: our brains are like sieves when it comes to retaining information from videos. Enter note-taking! Here’s how to do it effectively:

• List the main points: Write down key concepts, explanations, and illustrations as they appear in the video. Learning is reinforced by this.
• Make diagrams: Complex processes can be made easier to understand with the use of visual aids like flowcharts. Imagine it as transforming intangible concepts into tangible images!
• Use timestamps: Make a note of the timestamp for convenient access later if a specific section amazed or perplexed you.

Active learning replaces passive viewing when notes are taken. You’ll also have a helpful reference manual for upcoming tasks!

Sourcing Practical Projects to Apply Learned Concepts

Practical experience is the most effective method to reinforce your grasp of machine learning. While watching tutorials is great, the real magic happens when you put what you’ve learnt into practice! Think about these tactics:

• Keep up with the projects: Project-based tutorials are available on a lot of YouTube channels. Instead of just watching, try coding with them!
• Make your own initiatives: Determine which real-world issues you are interested in and consider how machine learning might be able to help. Do you want to forecast the cost of homes? Do it!
• Participate in contests: You can test your abilities against others while working on actual datasets in competitions hosted by platforms such as Kaggle.

Conclusion

That’s it, then! We’ve taken a fun trip through the best YouTube channels to learn Machine Learning, looking at everything from easy-to-follow videos to more complex ML lessons. These highly regarded machine learning channels on YouTube will help you become an expert in the vast field of machine learning.

Keep in mind that actively interacting with the content is more important for mastering machine learning than merely passively consuming it. Therefore, make sure you’re actively participating, whether you’re taking machine learning courses on YouTube or following along with real-world projects. Here are some concluding remarks:

Remain Inquisitive: Machine learning is always changing. Keep up with the most recent advancements by following popular ML content creators on YouTube.

Interact with the Community: Take part in conversations, ask questions, and do more than just observe and leave comments. The community that surrounds websites like YouTube is their best feature!

Diversify Your Learning: For a comprehensive grasp of machine learning concepts, mix your YouTube education with books and online courses.

The accessibility and diversity of the best YouTube channels to learn Machine Learning are what make them so appealing. There is something for everyone on YouTube, whether you’re searching for interactive machine learning lessons or in-depth ML courses. So, prepare to discover the mysteries of machine learning by grabbing your favourite snacks and clicking the subscribe button!

What You Should Do Next? Decide on a channel (or three!), establish some objectives, and begin your machine learning adventure right now. Before you know it, you will be making predictions if you put in the necessary effort and have the appropriate tools at your disposal.