Sklearn test train split||Machine Learning Tutorial||Part-9||Malayalam

This part of "Machine Learning Tutorial" in Malayalam covers:
Need for Test train split
Test train split using Test train split
Limitations of test train split

Overall scope of course
1. Introduction to Machine learning- Need for AI/ML, why to learn AI/ML, machine learning types, supervised, unsupervised and reinforced learning, application, difference between Human thinking Vs Machine thinking, difference between programming vs Machine learning.
2. Mathematics for Machine learning- Trigonometry, linear algebra, matrices, calculus & probability.
3.Python for Machine learning- variables, different libraries needed for data science such as numpy, pandas, matplotlib, etc
4. Deep-dive into machine learning- How ML algorithm works, the concept of cost function and gradient descent, practical examples for linear regression and Classifications, ML Algorithms and its usage.
5.Introduction to OpenCV- Image/video processing with OpenCV
6. Face recognition- Building a security alarm system using ML techniques

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[revathysadasivan]

Hi sir, if a new data is entered other than test data, how this machine will recognise that