Welcome to MLWithMe, your comprehensive guide to mastering Machine Learning from the ground up!

I have started an initiative on LinkedIn where I regularly share posts about Machine Learning. To make the content easily accessible and keep you updated on the latest posts, I'll be maintaining and extending the content right here in this repository.

Machine Learning is a vast field, and understanding it requires time and dedication. MLWithMe is designed to simplify this journey, breaking down complex concepts into manageable steps and establishing a strong foundation in the core principles of machine learning. And provides useful free resources available on the internet.

Before diving into the reality of Machine Learning (ML), it's essential to understand what it is and why it's gaining so much popularity nowadays. Getting a grasp of ML not only boosts your confidence but also sparks your interest in choosing this field. I encourage you to explore ML by researching on the internet, reading articles and blogs, you can also check out my Medium blog titled "What and Why is Machine Learning?" It provides straightforward insights into ML, its practical applications, and how it's used in the real world. This way you will get a good understanding about ML.

Once you've gained a basic understanding, you can confidently venture into the exciting world of ML and start your learning journey. Let's get started! 🚀

• Some familiarity with Python, even if you just know the basics of its syntax and fundamental operations. We'll be using Python for hands-on experience with mathematical functions, and a basic understanding of Python will suffice.
• Having done a bit of research on machine learning beforehand would be beneficial. While we won't cover 100% here, you'll gain an overview and discover useful resources. The hands-on work from scratch is something you'll need to tackle on your own.
• Need an exploring mindset. To truly understand ML, it's essential to explore and dive deeper into some topics. Merely running codes won't suffice; developing a curious mindset and personally delving into subjects lead to good comprehension.

Learning mathematics is crucial for mastering machine learning. Math enables us to grasp the inner workings of ML models, making concepts like linear algebra, statistics, and calculus essential. Think of it as the language machines speak. Embracing math in your ML journey empowers you to unlock the full potential of this exciting field.

The following are the key components in mathematics for ML.

• LinearAlgebra
• Probability
• Statistics
• Calculus

Learning Mathematics will get you some confidence about the field ML. Once you had a strong hold on basics of Maths you will be ready to engage further in the journey of learning ML..

Apply knowledge to real-world scenarios through hands-on projects.

Embark on your machine learning journey with MLWithMe, a repository tailored to empower you with the skills and knowledge needed to navigate the exciting landscape of machine learning. Let's learn, grow, and innovate together! 🤖✨

Feel free to connect with me on social platforms! I am always excited to engage with fellow learners, professionals, and enthusiasts in the field of machine learning.

Let's connect and share our knowledge and experiences. Feel free to reach out for discussions, or simply to say hello! 🚀