In my carrer i have started to know that how to learn data science by following thse steps
- Probability and Statistics
One needs to be very good at both these you need to be strong in both the areas where you can understand the more complex topics in statistics
This will help in understanding the data science even better
Basically machine learning is nothing but applying stastics through programming
You need to be aware of machine learning algorithms in details
Its not learning each and every algorithm that is present but whatever is learnt it needs to be learned at its core
Basically Machine learning consists of three types of problems.
- Super vised learning:Here the outcome labels are known to us already
- Unsupervised learning: Here the outcome is not known to us we need to group the data given to us into different clusters
- Reenforcement learning: Here the algorithms works on reward and actions.Based ont he actions it is rewarded correctly or not.
Basicaly it is used to solved for image or video data.It consists of neural netwroks which learns by backward propagation
It is cyclic process which learns by updating the weights