Start Machine Learning with hands on projects
Hack your way in
Start Machine Learning with hands-on projects
How you can start with hands-on projects from the beginning
“An exploring mind is the most precious gift in life and it’s very keen to learn without any judgmental eye.”― Euginia Herlihy
Who can learn?
If you are a Machine Learning enthusiast and keen to learn then it is never too late to start your journey in the field of Data Science & Machine Learning.
By the number of data multiplying exponentially day by day and many free resources available, it is a good opportunity for us to study the data and extract some meaningful output out of it.
But why is it so hard to get started?
For beginners like us, it is a challenging task to just getting started. Data Science and Machine Learning are the hottest topics among Computer Enthusiast, due to this there are many scattered resources over the internet which can easily deflect our path.
At its core, data science is a field of study that aims to use a scientific approach to extract meaning and insights from data
Machine learning, on the other hand, refers to a group of techniques used by data scientists that allow computers to learn from data.
If you just google search about any topics on Data Science and Machine Learning, you can get overwhelmed by the number of resources and it is very challenging to catch one road map and follow.
Motivation
So, in this post, I am going to share, how I self-started my journey by doing some hands-on projects and provide everyone with some sacred resources to study.
I will be sharing how you can get your hands dirty with some ML algorithms and Data.
Getting Started
First off, everyone can easily learn the introductory part by googling or by a simple YouTube search.
If you are like me and prefer visual + audio tutorials for better understanding then you can start with Google’s Machine Learning Recipes. It is a good resource to get started with some examples. From there you can learn about the Machine Learning algorithms and build some as well.
Grasp the concepts
Along the way, you can look into other resources as well and get a good grasp of What, How, and Why Machine Learning. It is not an overnight task, so learn to have some patience and gracefully feel the beauty of Data Science.
In every walk with Data Science one receives far more then he seeks.
— Anyesh
Due to a lot of resources available online, one should learn to find the rich and quality resources which fit their level.
For example: If you want to learn how some Algorithms look in action, try some small tutorials which use libraries, and develop something small. After that, you can learn about that algorithm by doing a simple google search: “math behind <algorithm>”.
It takes time but once you find a good resource that fits with you then you can learn easily.
Hands-on Projects after Basics
After some basic knowledge, you can learn about various other algorithms. It is not important for you to know everything from the beginning. You can just:
- Start with one and learn about it from various authors and resources. For example: Try searching “beginner guide to linear regression” in google and start with the first post you get.
- Create something out of it; something which motivates you and makes you feel happy. It is very important to stay motivated, that’s why reading + implementing that knowledge in some projects is very important. It helps you to see an actual output of what you have learned.
How did I start?
After some basics, I implemented a Gradient Descent: which is a learning algorithm in this project, which helped me understand how a Machine Learning model learns. Here you can plot two or more points anywhere and it tries to learn(reduce error) and best fit a line between those points by itself.
Interesting, isn’t it 😁? You can find an awesome YouTube video on this and a few other algorithms by coding train here.
And if you are a book person then, try reading Hands-on Machine Learning with sci-kit learn and Tensorflow.
Final Words
I really hope you will enjoy the journey. Always start with something small and keep growing.
One should never stop learning new things in this field. Every day new and interesting things are been researched so, keep learning and stay curious! 😄
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