Ensemble learning-Random forest||Malayalam||Machine Learning Course||Part-24

Ensemble learning-Random forest||Malayalam||Machine Learning Course||Part-24
This part of "Machine Learning Course" in Malayalam gives the concept of ensemble methods in machine learning combine the insights obtained from multiple learning models to facilitate accurate and improved decisions.
Random Forest is a popular classifier that contains a number of decision trees on various subsets of the given dataset and takes the average to improve the predictive accuracy of that dataset
Overall scope:
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

#machinelearningmalayalam#machinelearningalgorithm#randomforest#ensemblelearning#datascience

[soniyas]

I loved ur video sir... I am watching your video for the first time... But it is more understandable❤

[anilajoy]

Explanation with figures is really helping, thank you :)