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A Beginner’s guide to Ai:
Hi fams, so recently I attended a course from the best instructor of Ai as I have heard a lot about Mr Andrew Ng and wanted like you all to learn something out of my areas which i am currently working upon. Andrew Ng is the founder of deep learning.ai srartup and also a co-founder of Coursera from where I learned this course ,he has also been a co-founder and head of Google brain and also Cheif scientist at Baidu.
So i have decided to explain this beginners friendly guide in 4 parts, this is the 1 part the subsequent parts will come incoming weeks so stay tuned ;).
So as you know Ai has been transformating the world so and so,all these media,important publications headlines, in technology world ,all these hypes I am pretty sure you would have also been came across such news every once nowadays. But is it true? The thing is that there has been a start but the complexations of it are yet to dive in.
So basically, What is ai? the most simple terms would be making computers or machines functions the way human works.But Ai is not a simple topic but it is more of blend of many other terminologies which many people sometimes fail to understand. But for a beginners like us it can be stimulated in a mathematical function as we all are already aware about maths and the functions .If some1 doesn’t he/she can simply Google ; ) . In Ai we come to a topic machine learning. So the most commonly used type of machine learning is a type of Ai a simple maths function or logic that works from “A to B” or input to output mapping “A to B” called as Supervisearning where what is “A”? It is all the data we provide to a system and “B” is the perfect deployed ai model we get.Here the input A can be anything from speech,audio,video clips most importantly the data etc. In this way we can define Ai using machine learning for a simple understanding.But as we talked about it is a blend so what are they?
So what are some basic components or the terminologies of an Ai or what drives wholly a “Ai”-
If going by a human parts i can define them as it is my personal way for your better understanding.
Data -yes you may be surprised but this is the 1, the core of everything and the way it is analyzed is done under “Data science”.
Machine learning algorithms- the most important step by step process to follow.
3.Machine learning and in that the most important type is supervised learning.
Neural network or Artificial neural networks- heavily inspired from human brain but somewhat does not all do what a brain does, the larger the neural network the larger the growth of ai.
5.Deep learning the thinking process where all of thought process comes from , it is a more modern term for a neural networks.
But what is the blood that keeps running all above five components ,even having them there can’t be no such physical tasks can be acheived.. yes it is the superfast supervised computers with specialized processors such as graphic processing units which play a heavy part in getting the data,storing it and helping the ml engineers in deploying the ml models.
At last who are frontline heroes who accomplish these tasks the warriors what are they called in the techy world?
The major job roles are-
- A Software engineer obviously to carry out the long coding work, more than 50% of an ai team consists of sde.
- A Machine learning engineer who writes the softwares which are responsible for A to B mappings mostly the supervised learnings to our ml models.
- A Machine learning researcher, they are ones who studies and researchs about the projects tells the team what’s to be done, it is one of the toughest but the important job roles.
- Applied Machine learning scientists they are the one working between ml engineers and researchers and do’s somewhat boths task.
- Data Scientists whose world moves all around the data.
- Ai Product Managers who tells the current specifications of products which are more reliable and are in demand in industry.
So having these people around can start your journey on working on Ai but still since there are not much of these people around in the industry, we can start our work with handsome of people training them and making them suitable as according to needs.
So here I end with the 1 part I would be bringing the next 3 parts incoming weeks and forward our journey to the world of Ai.
Thankyou for your patient reading.
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