Maching Learning part_1
Let’s learn machine learning from beginning. I tried to write the blog simple as possible. Then you will understand about machine learning very well. Don’t miss to read my blogs 😊.
Let’s start 😊😊😊
Today I like to give a small introduction on Machine Learning. It will be helpful as a beginner .
Introduction
Let’s see the interconnection between machine learning, deep learning, artificial intelligence and data science.
As the picture above, Machine Learning is sub category of AI. And Deep Learning is sub category of Machine Learning. Data science covers the three concepts; AI, Machine Learning, and Deep Learning. Data science is about data connection and data analysis.
When machine learning came up to world?
In 1959
Why the machine learning is not popular at that time?
In 1959, there is no necessary processing power and computer facilities.
Nowadays, Machine Learning got hit due to having necessary processing power like CPU, GPU and computer facilities.
GPU- Graphics Processing Unit
How CPU and GPU affect to the machine learning?
GPU’s are extremely important in the world of machine learning. GPUs have around 200 times more processors per chip than CPUs. The flip side of this, however, is that whereas CPUs can perform any kind of computation, GPUs are tailored to only specific use cases, where operations have to be performed on vectors, which are essentially list of numbers.
About the platforms for create ML projects
Google cloud, AWS, Google CoLab and Azure are the platforms which makes easy for machine learning developers, data scientists and data engineers to take their ML projects. Google Core Lab provides RAM of 12 GB with maximum extension of 25 GB and disk space of 358.27 GB.
TPU- Tensor Processing Unit is an AI accelerator application-specific integrated circuit developed by the Google specifically for neural network machine learning.
Amazon Sagemaker is a cloud machine learning platform. It enables developers to create, train, and deploy machine learning models in the cloud.
Ler’s know about Machine Learning Applications
NetFlix — Users who watch A are likely to watch B. This is perhaps the most well known feature of a Netflix. Netflix uses the watch history of other users with similar tastes to recommend what you may be most interested in watching next so that you stay engaged and continue your monthly subscription for more.
Facebook — It introduces the face recognition for tagging the photo of you.
What does mathematical knowledge need in Machine Learning?
We have to have knowledge on Calculus, Algebra, Probability and Matrices.
If you are very much interested in machine learning. Use kaggle to improve your skills on macine learning and use twitter to read the research papers.
So that’s all for today’s blog. Hope you all gain some knowledge on machine learning
In next blog, I hope to write about 3 categorization of machine learning and python which we are going to use for machine learning. It will be interesting and if you don’t know anything about python, don’t worry about it. I hope to go from beginning 😊. More to go…
Have a nice day 😊 😊 😊
Author :
Zeena Youhan
Undergraduate ,
B.Sc. (Hons)in Software Engineering,
University of Kelaniya,
Sri Lanka.
