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The Complete Naive Bayes algorithm course with Python 2023

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The Complete Naive Bayes algorithm course with Python 2023, available at $49.99, has an average rating of 4.7, with 21 lectures, based on 13 reviews, and has 68 subscribers.

You will learn about Naive Bayes Numpy Matplotlib GaussianNB LogisticRegression train_test_split roc_curve auc DictVectorizer MultinomialNB BernoulliNB This course is ideal for individuals who are Anyone interested in Machine Learning. or Students who have at least high school knowledge in math and who want to start learning Machine Learning, Deep Learning, and Artificial Intelligence or Any people who are not that comfortable with coding but who are interested in Machine Learning, Deep Learning, Artificial Intelligence and want to apply it easily on datasets. or Any students in college who want to start a career in Data Science or Any people who want to create added value to their business by using powerful Machine Learning, Artificial Intelligence and Deep Learning tools. Any people who want to work in a Car company as a Data Scientist, Machine Learning, Deep Learning and Artificial Intelligence engineer. It is particularly useful for Anyone interested in Machine Learning. or Students who have at least high school knowledge in math and who want to start learning Machine Learning, Deep Learning, and Artificial Intelligence or Any people who are not that comfortable with coding but who are interested in Machine Learning, Deep Learning, Artificial Intelligence and want to apply it easily on datasets. or Any students in college who want to start a career in Data Science or Any people who want to create added value to their business by using powerful Machine Learning, Artificial Intelligence and Deep Learning tools. Any people who want to work in a Car company as a Data Scientist, Machine Learning, Deep Learning and Artificial Intelligence engineer.

Enroll now: The Complete Naive Bayes algorithm course with Python 2023

Summary

Title: The Complete Naive Bayes algorithm course with Python 2023

Price: $49.99

Average Rating: 4.7

Number of Lectures: 21

Number of Published Lectures: 21

Number of Curriculum Items: 21

Number of Published Curriculum Objects: 21

Original Price: $199.99

Quality Status: approved

Status: Live

What You Will Learn

  • Naive Bayes
  • Numpy
  • Matplotlib
  • GaussianNB
  • LogisticRegression
  • train_test_split
  • roc_curve
  • auc
  • DictVectorizer
  • MultinomialNB
  • BernoulliNB

Who Should Attend

  • Anyone interested in Machine Learning.
  • Students who have at least high school knowledge in math and who want to start learning Machine Learning, Deep Learning, and Artificial Intelligence
  • Any people who are not that comfortable with coding but who are interested in Machine Learning, Deep Learning, Artificial Intelligence and want to apply it easily on datasets.
  • Any students in college who want to start a career in Data Science
  • Any people who want to create added value to their business by using powerful Machine Learning, Artificial Intelligence and Deep Learning tools. Any people who want to work in a Car company as a Data Scientist, Machine Learning, Deep Learning and Artificial Intelligence engineer.

Target Audiences

  • Anyone interested in Machine Learning.
  • Students who have at least high school knowledge in math and who want to start learning Machine Learning, Deep Learning, and Artificial Intelligence
  • Any people who are not that comfortable with coding but who are interested in Machine Learning, Deep Learning, Artificial Intelligence and want to apply it easily on datasets.
  • Any students in college who want to start a career in Data Science
  • Any people who want to create added value to their business by using powerful Machine Learning, Artificial Intelligence and Deep Learning tools. Any people who want to work in a Car company as a Data Scientist, Machine Learning, Deep Learning and Artificial Intelligence engineer.

Are you ready to take your data science skills to the next level? If so, our comprehensive course on the Naive Bayes algorithm is just what you need! This course teaches you the theories, applications, and real-life examples of this powerful data science tool.

I have years of industry experience and will guide you every step of the way, from the basics to advanced concepts. With hands-on learning, you’ll work on real-life projects and use cutting-edge tools and technologies, such as Python and its famous libraries, like sci-kit-learn. my course is perfect for anyone looking to upskill, change careers, or simply expand their knowledge in data science.

In this course, you’ll learn how to implement Naive Bayes for solving various problems, including text classification, sentiment analysis, and spam filtering. You’ll also learn how to build and evaluate models for maximum accuracy. With interactive and self-paced learning, you’ll have the opportunity to put your newfound skills into practice as you work through real-life projects.

My course is designed to be flexible and self-paced so that you can learn at your own pace and on your schedule. And with my support team always available to help, you’ll always be on your own.

In addition to our comprehensive course, you’ll also have access to our extensive library of resources, including tutorials, guides, and notes, to help you further your understanding of the subject. Whether you’re just starting out or already familiar with Naive Bayes, our course is designed to meet your needs and help you reach your goals.

So, why wait? Enroll in our Naive Bayes course today and take the first step towards mastering one of the most powerful algorithms in data science. My course is perfect for anyone looking to enhance their data science skills, regardless of their current level of expertise.

This course is fun and exciting, but at the same time, we dive deep into  Naive Bayes. Throughout the brand new version of the course, we cover tons of tools and technologies, including:

  • Naive Bayes

  • Numpy

  • Logistic Regression.

  • Matplotlib

  • GaussianNB

  • train_test_split

  • roc_curve

  • auc

  • DictVectorizer

  • MultinomialNB

  • BernoulliNB

Moreover, the course is packed with practical exercises based on real-life examples. So not only will you learn the theory, but you will also get some hands-on practice building your models. There are several big projects in this course. These projects are listed below:

  • Diabetes project.

  • Data Project.

  • Sentiment Analysis

  • MNIST Project.

So why wait? Enroll now and take your understanding of Naive Bayes to the next level

Course Curriculum

Chapter 1: Introduction

Lecture 1: Course Structure

Lecture 2: IMPORTANT NOTES PLEASE DO NOT SKIP

Lecture 3: How to make the most out of this course

Lecture 4: What is classification

Chapter 2: Introduction to Naive Bayes classifier

Lecture 1: Basic theory of Naive Bayes algorithm

Lecture 2: Project 1 implementation Part 1

Lecture 3: Project 1 implementation Final Part

Lecture 4: Introduction to confusion matrix

Lecture 5: Confusion matrix implementation

Chapter 3: Sentiment analysis using Naive Bayes

Lecture 1: Introduction to sentiment analysis and Implementation part 1

Lecture 2: Implementation final Part

Chapter 4: Diabetes Project with Naive Bayes

Lecture 1: Introduction and Implementation

Chapter 5: Some other Naive Bayes algorithm

Lecture 1: Introduction to Bernoulli Naive Bayes

Lecture 2: Bernoulli Naive Bayes Implementation

Lecture 3: Introduction to Multinomial Naive Bayes

Lecture 4: Multinomial Naive Bayes Implementation

Lecture 5: Introduction to Gaussian Naive Bayes

Lecture 6: Gaussian Naive Bayes Implementation

Chapter 6: Fertility Project with Naive Bayes

Lecture 1: Introduction and Implementation

Chapter 7: Income prediction with Naive Bayes Algorithm

Lecture 1: Introduction and implementation

Chapter 8: Thank you

Lecture 1: Thank you

Instructors

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  • 2 stars: 1 votes
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  • 4 stars: 0 votes
  • 5 stars: 12 votes

Frequently Asked Questions


How long do I have access to the course materials?


You can view and review the lecture materials indefinitely, like an on-demand channel.


Can I take my courses with me wherever I go?


Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!

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