The Best Way to Learn Machine Learning in 2024

🔑High-level frameworks like PyTorch and TensorFlow are no longer the only way to solve complex machine learning problems.

🚀New tools have made the process of training a machine learning model much easier and more accessible.

🔍Focus on problem-solving and learning how to solve specific machine learning problems rather than just using tools.

👥Machine learning engineering is about problem-solving, not just using tools.

🗺️Follow a machine learning and AI roadmap to acquire the necessary skills and knowledge.

Are PyTorch and TensorFlow still important for machine learning?

—While PyTorch and TensorFlow are still widely used, there are now many other tools and frameworks that make the process of training a machine learning model much easier.

What are some examples of new tools for machine learning?

—Examples of new tools include Ultralytics YOLOv8 for object detection and Teachable Machine for image classification.

Should I focus on learning tools or problem-solving in machine learning?

—To become a successful machine learning engineer, it is important to focus on problem-solving and learning how to solve specific machine learning problems.

Is there a roadmap for learning machine learning and AI?

—Yes, there is a machine learning and AI roadmap that provides a step-by-step guide and specific resources for acquiring the necessary skills.

Where can I find the machine learning and AI roadmap?

—The machine learning and AI roadmap can be found in one of Felipe's previous videos.

00:00Introduction to the best way to learn machine learning in 2024.

02:52Examples of new tools for machine learning, such as Ultralytics YOLOv8 and Teachable Machine.

03:23Importance of focusing on problem-solving rather than just using tools in machine learning engineering.

03:59Invitation to check out Felipe's previous video on the machine learning and AI roadmap.