machine_learning

This Machine Learning repository provides implementation of various machine learning algorithm in practical way such as supervised learning, unsupervised learning and etc.

Machine Learning

• Machine Learning is defined as "A computer program is said to learn from experience E with respect to some class of tasks T and performance measure P if its performance at tasks in T, as measured by P, improves with experience E.
• Machine Learning is a branch of AI that develops algorithms by learning the hidden patterns of datasets used it to make predictions on new similar type data, without exlicity programmed for each task.

•          |___________________
  

• -------------| | | ML Model |------------> prediction/program

•            |                   |
  

• -------------->|___________________|
• output

Types of Machhine Learning

1. Supervised Learning

Categories of Supervised Learning

• 1.1 Classification
• 1.2 Regression

Algorithms for Supervised Learning

• logistic regression, SVM, random forest, decision tree, KNN, naive bayer
• linear regression, polynomial regression, lasso regression

2. Unsupervised Learning

Categories of Unsupervised Learning

• 2.1 Clustering
• 2.2 Association

Algorithms for Unsupervised Learning

• K-mean clustering, mean-shift,
• Apriori Algo,

3. Reinforcement Learning

Algorithms for Reinforcement Learning

• Q-learning, SARSA, Deep Q-learning

4. Semi Supervised Learning

5. Generative AI

6. Transfer Learning