Hello Machine learning Freaks!

I going to discuss about The Basic Machine Learning algorithms

============SVM=============

1. SUPPORT VECTOR Classifier SVM uses for the classification of the data
2. SUPPORT VECTOR REGRESSION SVR used for the prediction of the feature data (Regression)

=================================================================================== https://en.wikipedia.org/wiki/Mean_squared_error https://en.wikipedia.org/wiki/Support-vector_machine Once go through this link

==================DECISION TREE========================================================= 3. Decision Tree Classifier https://www.saedsayad.com/decision_tree.htm Go through this link

4. Decision Tree Regressor
   https://scikit-learn.org/stable/modules/generated/sklearn.tree.DecisionTreeRegressor.html -->>>go through this link https://www.geeksforgeeks.org/python-decision-tree-regression-using-sklearn/ ----->> here also

=======================Random Forest===================================================== 5.RandomForestClassifier https://medium.com/machine-learning-101/chapter-5-random-forest-classifier-56dc7425c3e1 https://towardsdatascience.com/the-random-forest-algorithm-d457d499ffcd

6.RandomForestRegressor https://towardsdatascience.com/random-forest-in-python-24d0893d51c0

=====================K-Nearest-Nighbors========================================== 7.KNN CLASSIIFER https://www.saedsayad.com/k_nearest_neighbors.htm 8.KNN Regressor-----Coming Soon

=================================Logistic Regressor=============================== https://machinelearningmastery.com/logistic-regression-for-machine-learning/ https://towardsdatascience.com/machine-learning-part-3-logistics-regression-9d890928680f

==================================Naive Bayes======================================== http://scikit-learn.org/stable/modules/generated/sklearn.naive_bayes.GaussianNB.html

Difference Between the Classification and Regression

===========================================CLASSIFICATION=========================== 1.classification means the classes it will have the calsses in the data like(male, female, 0,1) 2.classicification says about the accuracy of the data in metrices 3.Classification have confusion matrix 4.classification for only separete the data into different classes

==========================================Regression================================ 1.Regression means the presicting the future data like(StockMarket prediction, House rate, etc...) 2.Regression says about error in the data

=============================================CONFUSION MATRIX==============================
https://www.dataschool.io/simple-guide-to-confusion-matrix-terminology/

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