How I’d Learn Machine Learning in 2024 (If I Were Starting Over)

In this video, I walk you through the 2024 Machine Learning Roadmap, designed to help you learn ML effectively using industry-standard tools and frameworks. Whether you're a complete beginner or looking to sharpen your skills, this roadmap will guide you through key ML concepts, practical projects, and advanced techniques.

Key Topics Covered:

1. Building a strong foundation in machine learning with Python
2. Mastering essential ML concepts: Transformers, Gradient Descent, and Attention Mechanisms
3. Hands-on projects using real-world datasets to practice ML
4. Learning deep learning frameworks like PyTorch to build powerful neural networks and how major applications like Tesla Autopilot, Uber’s Pyro, and Hugging Face’s Transformers are built on PyTorch
5. Scaling ML models with cloud platforms like AWS and Azure
6. Preparing for ML Engineer roles by mastering MLOps and end-to-end pipelines

By following this roadmap, you’ll learn how to navigate ML’s core concepts, from simple linear regression to advanced deep learning with PyTorch. These skills are key to landing roles as a machine learning engineer, data scientist, or AI developer.

📖 MACHINE LEARNING COURSES
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🔑 Key Topics Covered:
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0:00 - Introduction
0:22 - State of AI
2:23 - Foundational Machine Learning Course
2:52 - Key Machine Learning Concepts
5:00 - Hands-On ML Experience
6:08 - Build Advanced Machine Learning Skills
7:22 - Prepare for Machine Learning Roles

🚀 Join me on #100DaysOfML
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✨ Hashtags ✨

[GenZ_Coder_]

I was just about to message you on LinkedIn to express how much I love your content and to encourage you to keep creating video lectures on YouTube. And then I saw your new video—perfect timing!👍

[rameshkumaran]

Good to see you back after a long gap of around one year. 😊

[siddhantrao]

Pls make a video for masters programme in ai and ml in canada and usa

[ayush]

Why did you stopped 100 days of machine learning series ?

[ahthyagaraj]

Is it still relevant to learn ML and its core mathematical concepts, given that LLMs are just an API call away?

[brandonmartinez]

To enter the job market in machine learning, it is essential to understand the fundamentals of artificial intelligence and models like GPT. There are 4-month courses and bootcamps that cover these concepts.

To transition into machine learning operations roles, is it necessary to delve deeply into machine learning, or is a basic understanding sufficient to quickly move to projects involving generative AI and cloud-based machine learning operations? What projects can provide the most learning and attract recruiters' attention?

Additionally, do you think the ability to reproduce and share results with data interpretation, using tools like Quarto with R and Python, will hold significant weight in the future? What machine learning projects would be most beneficial for a beginner to advance their learning and achieve employment or professional growth?

[j.r.r.tolkien]

Please use external mic next time. It was hard to understand

[haroldmurff]

Yesss😂 keep this coming...love there information....

[dinesh_hewage]

can we find remote ML jobs from India?.

[sreekartammana]

Finally she remembered that she has a YT channel😶‍🌫️

[CantPickTheNameIwant]

It's a BS regarding the availability of jobs for entry-level engineers. You will struggle hard to get your first job and be ready to spend more than a year in search