Comprehensive Feature Engineering for Machine Learning

Comprehensive Feature Engineering for Machine Learning, available at $54.99, with 39 lectures, 5 quizzes.

You will learn about Master techniques to clean and preprocess raw data for analysis. Apply various methods to handle and encode outliers and missing values. Implement scaling and transformation strategies to enhance data quality. Perform feature extraction from different data types and optimize models. This course is ideal for individuals who are Beginners interested in starting a career in data science or machine learning. or Data analysts and professionals looking to refine their feature engineering skills. or Students and researchers who require advanced data manipulation techniques for projects. or IT professionals seeking to understand data preprocessing to improve system insights. It is particularly useful for Beginners interested in starting a career in data science or machine learning. or Data analysts and professionals looking to refine their feature engineering skills. or Students and researchers who require advanced data manipulation techniques for projects. or IT professionals seeking to understand data preprocessing to improve system insights.

Enroll now: Comprehensive Feature Engineering for Machine Learning

Summary

Title: Comprehensive Feature Engineering for Machine Learning

Price: $54.99

Number of Lectures: 39

Number of Quizzes: 5

Number of Published Lectures: 39

Number of Published Quizzes: 5

Number of Curriculum Items: 44

Number of Published Curriculum Objects: 44

Original Price: $19.99

Quality Status: approved

Status: Live

What You Will Learn

Master techniques to clean and preprocess raw data for analysis.
Apply various methods to handle and encode outliers and missing values.
Implement scaling and transformation strategies to enhance data quality.
Perform feature extraction from different data types and optimize models.

Who Should Attend

Beginners interested in starting a career in data science or machine learning.
Data analysts and professionals looking to refine their feature engineering skills.
Students and researchers who require advanced data manipulation techniques for projects.
IT professionals seeking to understand data preprocessing to improve system insights.

Target Audiences

Beginners interested in starting a career in data science or machine learning.
Data analysts and professionals looking to refine their feature engineering skills.
Students and researchers who require advanced data manipulation techniques for projects.
IT professionals seeking to understand data preprocessing to improve system insights.

Unlock the potential of your data with Miuul’s targeted, high-impact course designed to equip you with the essential skills in feature engineering. This course teaches you how to clean, process, and enhance raw data, transforming it into a format ready for advanced machine learning models. You will master the techniques to cleanse and prepare raw data, making it ideal for deeper analysis and modeling. Additionally, you will explore advanced feature techniques such as handling outliers, encoding categorical variables, and scaling features to enhance model accuracy and performance.

What You Will Learn

Over the course of 4.5 hours of focused content, this course takes you straight to the heart of feature engineering. The learning experience is made interactive with quizzes that reinforce the concepts taught in each section, helping you to engage thoroughly with the material. By the end of the course, you will earn a certificate of completion that adds significant value to your professional profile.

Course Features

This course offers quick skill enhancement, upgrading your abilities in data processing significantly. The methods taught are highly valued in tech and data science roles across industries, making this training not only relevant but also practical. You can learn at your convenience, proceeding at your own pace and fitting the learning into your schedule. The course includes all the resources you need to understand and apply feature engineering effectively.

Why This Course?

Whether you are looking to advance in your current role, tackle new challenges, or lead data-driven projects, this course is your gateway to unlocking the power of data. Equip yourself with valuable skills crucial in today’s data-centric job market! The course structure includes a detailed exploration of techniques for dealing with outliers, missing values, encoding strategies, and feature scaling, alongside hands-on practice with the Titanic dataset to apply what you’ve learned. A comprehensive quiz at the end helps to consolidate your knowledge and earn your certificate.

Enroll Now

Take the first step towards mastering feature engineering and start transforming data into actionable insights today by enrolling in Miuul’s transformative course!

Course Curriculum

Chapter 1: Introduction

Lecture 1: Course Materials

Lecture 2: Feature Engineering and Data Pre-Processing

Chapter 2: Outliers

Lecture 1: Introduction to Outliers

Lecture 2: Capturing Outliers

Lecture 3: Defining a Function to Detect Outliers

Lecture 4: Grabbing Column Names

Lecture 5: Accessing Outliers

Lecture 6: Solving the Outlier Problem

Lecture 7: Local Outlier Factor

Chapter 3: Missing Values

Lecture 1: Introduction to Missing Values

Lecture 2: Capturing Missing Values

Lecture 3: Solving the Missing Value Problem

Lecture 4: Assigning a Value to Categorical Variables

Lecture 5: Predictive Assignments

Lecture 6: Analyzing the Structure of Missing Data

Lecture 7: Analyzing Missing Values with Dependent Variable

Chapter 4: Encoding & Scaling

Lecture 1: Label Encoding

Lecture 2: Label Encoding – Application

Lecture 3: One-Hot Encoding

Lecture 4: One-Hot Encoding – Application

Lecture 5: Rare Encoding

Lecture 6: Rare Encoding – Application

Lecture 7: Rare Encoding – Function

Lecture 8: Feature Scaling

Lecture 9: Feature Scaling – Application

Chapter 5: Feature Extraction

Lecture 1: Introduction to Feature Extraction

Lecture 2: Binary Features

Lecture 3: Text Features

Lecture 4: Regex Features

Lecture 5: Date Features

Lecture 6: Feature Interactions

Chapter 6: Applications with Titanic Dataset

Lecture 1: Introduction

Lecture 2: Outliers

Lecture 3: Missing Values

Lecture 4: Label Encoding

Lecture 5: Rare Encoding

Lecture 6: One-Hot Encoding

Lecture 7: Standard Scaler

Lecture 8: Model

Chapter 7: Final Questions

Instructors

Miuul Data Science & Deep Learning
Data Science Team of Miuul.com

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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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