Starting with Statistical/Machine Learning
This blog talks about the basics of MACHINE LEARNING and how to get started with it.
INTRODUCTION
Mathematics has been the part of mankind since humans started using their rational abilities and it has done wonders so many times. We all know that it is a very powerful tool for so many explorations. It has helped humans LEARN BETTER. Things like stats, calculus, linear algebra, etc. are widely used in real life applications.
Computers or Computational ability of machines have opened a world to us. I don’t even have to tell you what miracles the modern day computers can do, be it a smart phone or a workstation. The capabilities and computational scope of these devices are approaching up exponentially. Machines can calculate toughest of problems in a lightening fast speed and way more accurate than a normal human can.
Machine Learning is in effect the convergence of MATHS and COMPUTERS. Making computers use the logic of mathematics and then applying it to solve and compute results to some problems which if done by humans can take a long time and the results might not be accurate enough is what the crux of MACHINE LEARNING.
STATISTICAL/MACHINE LEARNING
Wikipedia says “Statistical/Machine learning is the scientific study of algorithms and statistical models that computer systems use to perform a specific task without using explicit instructions, relying on patterns and inference instead.”
In simple terms, Statistical Learning means applying statistical models(discussed below) on a specific data which helps us to make use of that data.
Machine Learning Algorithms
- Linear Regression
- Logistic Regression
- Decision Tree
- SVM
- Naive Bayes
- kNN
- K-Means
- Random Forest
- Dimensionality Reduction Algorithms
Where to start from ?
Getting into Artificial Intelligence or Data Science requires a good understanding of each of the field before actually enrolling into it. Understanding what things are at the root level and then deciding whether it is your interest or not is very important.
Once you are done with the research and understanding part, learning Machine Learning requires a good understanding of mathematical concepts.
You can refer to these links to learn relevant Mathematical Concepts :
Book : https://mml-book.github.io/book/mml-book.pdf
course : ML course
At the end, I would suggest everyone reading this that the path of learning anything is never too easy. Sometimes it is exciting and sometimes it becomes boring, consistency is what decides how far you go.
Be curious, Keep Learning
Bahauddin Aziz
