Unsupervised Learning in Machine learning|| Explanation in Malayalam

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Unsupervised Learning in Machine learning|| Non Technical explanation in Malayalam

Unsupervised learning refers to the use of artificial intelligence (AI) algorithms to identify patterns in data sets containing data points that are neither classified nor labeled.

The algorithms are thus allowed to classify, label and/or group the data points contained within the data sets without having any external guidance in performing that task. Chatbots, self-driving cars, facial recognition programs, expert systems and robots are among the systems that may use either supervised or unsupervised learning approaches, or both

The goal of unsupervised learning is to find the underlying structure of dataset, group that data according to similarities, and represent that dataset in a compressed format.
In this session, we understand supervised learning and its types like clustering/grouping, dimensionality reduction, Matrix factorization, Anomaly detection
The full Course Plan:
This covers the below Topics:
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 Agorithams 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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its very informative sir... expecting more videos...thank you

sudheerbabueledath
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ഇതൊക്കെ എന്നാണ് കമ്പ്യൂട്ടറിൽ ചെയ്യുന്നത് കാണുക

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