Data Science Full Course For Beginners | Python Data Science Tutorial | Data Science With Python In this python machine learning tutorial for beginners we will build email spam classifier using naive bayes algorithm. We will use sklearn CountVectorizer to convert email text into a matrix of numbers and then use sklearn MultinomialNB classifier to train our model. The model score with this approach comes out to be very high (around 98%). Sklearn pipeline allows us to handle pre processing transformations easily with its convenient api. In the end there is an exercise where you need to classify sklearn wine dataset using naive bayes. #MachineLearning #PythonMachineLearning #MachineLearningTutorial #Python #PythonTutorial #PythonTraining #MachineLearningCource #NaiveBayes #sklearntutorials #scikitlearntutorials Dataset: https://github.com/codebasics/py/blob... Exercise: https://github.com/codebasics/py/blob... Code:https://github.com/codebasics/py/blob... Exercise solution: https://github.com/codebasics/py/blob... Topics that are covered in this Video: 00:00 explore spam email dataset 02:33 sklearn CountVectorizer 04:30 types of naive bayes classifiers 05:23 sklearn MultinomialNB classifier 06:48 sklearn pipeline 09:35 Exercise