If you're interested in machine learning but don't know where to start, you're not alone. Machine learning is a complex and rapidly evolving field that requires a solid foundation in mathematics, statistics, and programming. Unfortunately, there is a plethora of resources available online and you may feel intimidated and confused. You may ask yourselves, "Is Machine Learning the right field for me?".
To answer that question, you must first clearly understand what Machine Learning is and how one would go about learning it. We have designed a series of YouTube videos for precisely this purpose. These videos will help you in your journey irrespective of your programming experience.
This is a series of 8 videos.
Video 1: Introduction to Python
Arguably the easiest and most beginner-friendly programming language to learn, learning Python would be the first step in your journey through the world of Machine Learning.
Start learning about Python by watching the first video.
Video 2: Introduction to Pandas and Numpy
Pandas and Numpy are two very important libraries of Python. They are widely used in Data Science and will help you manipulate your data while training your Machine Learning Models. Learn about them here.
Video 3: Welcome to Matplotlib and Plotly
To understand what is going on with your data you need to visualize it. Matplotlib and Plotly are two libraries which help you achieve exactly that. They are widely used for showcasing projects on websites and Jupyter notebooks. Familiarize yourself with these libraries by watching this video.
Video 4: Scikit-Learn and Streamlit
Scikit-Learn is a widely used Python library for hands-on Machine Learning. Build your models and deploy them using Streamlit — which allows you to showcase your projects on a website without having to learn web development. Learn about them here.
Video 5: Github/Projects
Confused about what projects to make? Watch the video below and get a few insights, alongside learning how to share your code on Github — a revolutionary platform that strengthened the coding community. Watch this video to get started.
Video 6: Intro to Deep Learning and Neural Networks
Two "fancy" terms that you may have come across while reading articles or talking to people about Machine Learning. We've covered them in the following video and it's not hard to understand what they mean! We've also covered a basic overview of how they work in this video.
Video 7: The Machine Learning Glossary
Trying to understand an article or a lecture on Machine Learning but it doesn't make sense? Familiarizing yourself with a few simple terms might help. Boost your confidence and understanding by watching this video now!
Video 8: Introduction to Kaggle
The most important and helpful platform that will help you progress through your Machine Learning Journey. Be it datasets, competitions or access to Jupyter Notebooks with GPUs, Kaggle always pulls through. Watch this video to learn about Kaggle.
This covers an overview of our Machine Learning series. So what are you waiting for? Start watching our playlist now!
Who we are
Ansh Singhal and Gautam Menon, two students pursuing B.E. in Computer Science and Engineering(Artificial Intelligence and Machine Learning) at M S Ramaiah Institute of Technology, Bangalore, working on an initiative to promote Machine Learning and Data Science under the mentorship of Harsh Singhal, Head of Data Science and Machine Learning at Koo.