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The Complete Linear and Logistic Regression Course in Python

  • Development
  • Apr 25, 2025
SynopsisThe Complete Linear and Logistic Regression Course in Python,...
The Complete Linear and Logistic Regression Course in Python  No.1

The Complete Linear and Logistic Regression Course in Python, available at $49.99, has an average rating of 5, with 27 lectures, based on 6 reviews, and has 47 subscribers.

You will learn about Tensorflow Tensorboard pandas ReLU activation function. Seaborn Google Colab Import data from the UCI repository. scikit-learn Logistic Regression. Linear Regression. numpy pickle tempfile Lasso and Ridge Regression Elastic Net Regression Multiple and multivariate linear regression TensorFlow Keras API 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 Linear and Logistic Regression Course in Python

Summary

Title: The Complete Linear and Logistic Regression Course in Python

Price: $49.99

Average Rating: 5

Number of Lectures: 27

Number of Published Lectures: 27

Number of Curriculum Items: 27

Number of Published Curriculum Objects: 27

Original Price: $199.99

Quality Status: approved

Status: Live

What You Will Learn

  • Tensorflow
  • Tensorboard
  • pandas
  • ReLU activation function.
  • Seaborn
  • Google Colab
  • Import data from the UCI repository.
  • scikit-learn
  • Logistic Regression.
  • Linear Regression.
  • numpy
  • pickle
  • tempfile
  • Lasso and Ridge Regression
  • Elastic Net Regression
  • Multiple and multivariate linear regression
  • TensorFlow Keras API
  • 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 interested in Machine Learning, Deep Learning, and Artificial Intelligence? Then this course is for you!

    A software engineer has designed this course. With the experience and knowledge I gained throughout the years, I can share my knowledge and help you learn complex theories, algorithms, and coding libraries.

    I will walk you into the world of the Naive Bayes Algorithm. These are fundamental concepts in machine learning, deep learning, and artificial intelligence. Understanding these basic concepts makes it easier to understand more complex concepts in machine learning, deep learning, and artificial intelligence. There are no courses out there that cover Naive Bayes Algorithm. However, Naive Bayes Algorithm techniques are used in many applications. So it is essential to learn and understand Linear and Logistic Regression. With every tutorial, you will develop new skills and improve your understanding of this challenging yet lucrative sub-field of Data Science.

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

  • Google Colab

  • Scikit-learn

  • Logistic Regression.

  • Linear Regression.

  • Seaborn

  • Lasso and Ridge Regression

  • Keras.

  • Pandas.

  • TensorFlow. 

  • TensorBoard

  • Matplotlib.

  • Elastic Net Regression

  • Import data from the UCI repository.

  • Multiple and multivariate linear regression.

  • TensorFlow Keras API

  • 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.

  • Breast Cancer Project.

  • Housing project.

  • MNIST Project.

  • By the end of the course, you will have a deep understanding of Linear and Logistic Regression, and you will get a higher chance of getting promoted or a job by knowing Linear and Logistic Regression.

    Course Curriculum

    Chapter 1: Introduction

    Lecture 1: Course Structure

    Lecture 2: IMPORTANT NOTES PLEASE DO NOT SKIP

    Lecture 3: How to make out of this course

    Lecture 4: What is regression?

    Chapter 2: Linear Regression Theory and Practice

    Lecture 1: Introduction to Linear regression

    Lecture 2: Linear Regression Implementation

    Lecture 3: Introduction to multiple and multivariate linear regression

    Lecture 4: Simple linear regression using TensorFlow Keras

    Lecture 5: Multiple and multivariate linear regression Implementation Part 1

    Lecture 6: Multiple and multivariate linear regression Implementation Part 2

    Lecture 7: Multiple and multivariate linear regression Implementation Final Part

    Chapter 3: Logistic Regression Theory and Practice

    Lecture 1: Introduction to classification

    Lecture 2: Introduction to Logistic Regression

    Lecture 3: Logistic Regression implementation Part 1

    Lecture 4: Logistic Regression implementation Part 2

    Lecture 5: Logistic Regression Implementation Final part

    Chapter 4: Advanced Linear and Logistic Regression

    Lecture 1: Housing data Implementation part 1

    Lecture 2: Housing data Implementation Part 2

    Lecture 3: Housing data implementation Part 3

    Lecture 4: Housing data implementation Part 4

    Lecture 5: Housing data implementation Part 5

    Lecture 6: Housing data implementation Part 6

    Lecture 7: Housing data implementation Part 7

    Lecture 8: Housing data implementation Final Part

    Lecture 9: Breast Cancer project Implementation with Logistic Regression

    Chapter 5: Logistic Implementation with Diabetes Project

    Lecture 1: Introduction and Implementation

    Chapter 6: Thank you

    Lecture 1: Thank you

    Instructors

  • The Complete Linear and Logistic Regression Course in Python  No.2
    Hoang Quy La
    Electrical Engineer
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  • 5 stars: 6 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!