**Data Science and Machine Learning Series: Bayes Theorem and the Naive Bayes Classifier**

English | MP4 | AVC 1280×720 | AAC 44KHz 2ch | 2h 26m | 311 MB

Master Bayes Theorem and the Naive Bayes classifier in this course within the Data Science and Machine Learning Series. Follow along with machine learning expert Advait Jayant through a combination of lecture and hands-on to become competent with these very powerful algorithms using the Python pandas and numpy libraries..

The following seven topics will be covered in this Data Science and Machine Learning course:

- Introducing Bayes Theorem. Become competent with Bayes Theorem in this first topic in the Data Science and Machine Learning Series. Learn about this powerful probability theorem along with posterior probability.
- Using Bayes Theorem for Spam Filtering. Use Bayes Theorem for Spam Filtering in this second topic in the Data Science and Machine Learning Series. Follow along with Advait and use this theorem for classification in identifying spam emails.
- Using Bayes Theorem for Disease Detection. Use Bayes Theorem for Disease Detection in this third topic in the Data Science and Machine Learning Series. Follow along with Advait and use this theorem for the classification of positive and negative lab tests.
- Introducing the Naive Bayes Classifier. Become competent with the Naive Bayes Classifier in this fourth topic in the Data Science and Machine Learning Series. Follow along with Advait and perform text classification using Naive Bayes.
- Using Naive Bayes for Mushroom Classification in Python. Use Naive Bayes for Mushroom Classification in this fifth topic in the Data Science and Machine Learning Series. Follow along with Advait and practice using Naive Bayes in Python. Use the numpy and pandas libraries. You will love mushrooms by the end of this session!
- Using Naive Bayes for Text Classification and Laplace Smoothing. Use Naive Bayes for Text Classification and Laplace Smoothing in this sixth topic in the Data Science and Machine Learning Series. Follow along with Advait and learn how Laplace Smoothing can improve the accuracy of the Naive Bayes classifier.
- Using Naive Bayes for SMS Spam Filtering. Use Naive Bayes for SMS spam filtering in this seventh topic in the Data Science and Machine Learning Series. Follow along with Advait and implement a spam detection machine learning model using Python and the numpy and pandas libraries.

**Table of Contents**

1 Introducing Bayes Theorem

2 Using Bayes Theorem for Spam Filtering

3 Using Bayes Theorem for Disease Detection

4 Introducing the Naive Bayes Classifier

5 Using Naive Bayes for Mushroom Classification in Python

6 Using Naive Bayes for Text Classification and Laplace Smoothing

7 Using Naive Bayes for SMS Spam Filtering

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