How you can become a Computer Vision Engineer - step by step Road Map.
What does it take to be Computer Vision Specialist ?
When I started to learn computer vision I came across many challenges, I guess we all get most of them as we are about to start something very new.
Never taught at school or our college, so here comes the exact problem- where to start from?
Now, it does not matter from which education background you belong, if there is an urge in you to learn this technology, then yes you can start it from now.
First of all, let me just be clear about few things before you start your computer vision journey.
What will give you more advantage over other learners -
- prior experience with programming languages like - Python, C++ or Java
- Good with Linear Algebra, Calculus, Statistics and Probability.
- Data Structures and Algorithms.
When it comes to learning you should never hesitate as learning is the only tool which you can use to create better outputs from your experiences and knowledge.
In today's article I will help you to start with the most ignored topics while studying Artificial Intelligence - Mathematics!
Topics to cover:
1. Linear Algebra - for better learning on topics about linear algebra I can suggest the few website which will provide you free of cost content to learn and create better foundation.
For interactive learning - https://www.3blue1brown.com
The above shared link hold the best content and if you will cover linear algebra from these website, that will enough to start with foundations of Computer Vision.
2. Calculus - when it comes to calculus we can use the same resources, in addition to that we can also check some of the mobile applications too.
Like Byju's app for learning is great for learning linear algebra and Calculus.
3. Statistics - The most interesting field which can be used with any kind of Data science job.
Statistics can be learned from the above resources too but what I personally suggest to opt with Udacity's free statistics course.
(These are short courses on statistics)
Stay Tuned for more on this journey to become Computer Vision Specialist.
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